Patient storm tracker and visualization processor

ABSTRACT

A patient monitoring system is described herein. In one example, the patient monitoring system comprises at least one processor programmed to generate an image which displays a patient condition as color weather radar on a map. In some examples, at least one monitored condition is positioned on the map so that the weather image expands, develops or moves over the condition.

This application claims the benefit of U.S. Provisional Application Ser.No. 61/770,919 filed Feb. 28, 2013, the contents of which are herebyincorporated by reference, and U.S. Provisional Application Ser. No.61/770,971 filed Feb. 28, 2013, the contents of which are herebyincorporated by reference. This application is a continuation-in-part ofU.S. patent application Ser. No. 13/677,295 filed Nov. 14, 2012, thecontents of which are hereby incorporated by reference. This applicationis also related to U.S. patent application Ser. No. 14/193,700, filedFeb. 28, 2014, titled “Parallel Human Time Matrix Image of Causation,”the entire contents of which are hereby incorporated by reference.

Human pathophysiology is highly complex and it is very difficult forphysicians and nurses to timely detect sepsis in the many settings. U.S.Pat. Nos. 8,241,213, 8,152,732, 7,758,503, 7,398,115 and 7,081,095, aswell as U.S. patent application Ser. Nos. 12/437,417, 12/437,385,12/629,407, 13/677,291, and 13/677,288 (the entire contents of each ofthese applications are incorporated by reference as if completelydisclosed herein) disclose processor methods, processing systems, andpatient monitors for timely detection, identification, quantification,tracking, and generation of dynamic displays of sepsis and otherconditions. These patents and applications provide additional backgroundfor the present subject matter.

U.S. patent application Ser. No. 13/677,295, entitled “PathophysiologicStorm Tracker”, filed Nov. 14, 2012 discloses processor based methodsand processor systems in which displays of sepsis are presentedmetaphorically as dynamic images similar to color weather radar. The useof the color weather radar metaphor connects the user's knowledge aboutweather patterns which, like sepsis, may over time; grow, spread,worsen, move, morph into another condition, evolve, aggregate, disperse,improve, recover, recur and recover again across clinical and/orcompartmental regions or spaces. These disclosed displays identify forexample; onset, dynamic severity, dynamic progression, dynamicrelationships to other events (such as medications) and/or procedures ina format which virtually all adults can readily understand. The use ofthe color weather radar metaphor takes advantage of the user's knowledgeabout dynamic processes to flatten the learning curve of sepsisdynamics. The color weather radar metaphoric images of sepsis and otherconditions of the aforementioned techniques as well as the presenttechniques renders the complexity of sepsis more readily interpretableby those with limited training to empower a larger group of individuals(including the patient or the patients family) to enhance surveillanceand mitigate the effects of a less than optimally attentive or trainedhealthcare worker.

BACKGROUND SUMMARY

Embodiments of the present disclosure provide improved and alternativesepsis motion image visualizations.

BRIEF DESCRIPTION OF THE DRAWINGS

Various embodiments will be described hereinafter with reference to theaccompanying drawings. These embodiments are illustrated and describedby example only, and are not intended to limit the scope of thedisclosure. In the drawings, similar elements may have similar referencenumerals.

FIG. 1 depicts a condition-centric storm tracking map for sepsis for asingle patient shown at a specific point in time.

FIG. 2 depicts a condition-centric patient storm tracking map for sepsisincluding the borders of clinical space for clarification.

FIG. 3 depicts a condition-centric patient storm tracking map for sepsisincluding both clinical space borders and patient storm overlaysdepicting areas of increasing perturbation and areas of recovery.

FIG. 4 is a condition-centric patient storm tracking map background forsepsis showing pattern relationships.

FIG. 5 depicts a general patient condition map without reference to aspecified condition.

FIG. 6 depicts a patient storm tracking map in which weather moves fromleft-to-right within vertically stacked areas of clinical space—in thiscase showing a patient exhibiting the symptoms of hemodynamic shock.

FIG. 7 depicts a condition-centric patient storm tracking map for sepsisusing a hexagon-based weather layer.

FIG. 8 depicts a hexagon-based patient storm cell derived from aseverity profile.

FIG. 9 depicts a property-level hexagon sub-visualization.

FIG. 10 is a force and limit diagram for a condition-centric patientstorm tracking map for sepsis.

FIG. 11 is a wireframe display of the weather layer on thecondition-centric patient storm tracking map for sepsis.

FIG. 12 depicts a historical patient storm tracking map for sepsis for apatient diagnosed with sepsis.

FIG. 13 depicts a historical patient storm tracking strip map for sepsisfor a patient diagnosed with sepsis.

FIG. 14 depicts a historical patient storm tracking map for sepsis for asepsis patient with rapid acceleration followed by recovery.

FIG. 15 depicts a historical patient storm tracking map for sepsis for apatient which exhibits CHF.

FIG. 16 depicts a historical patient storm tracking map for sepsis withoverlays highlighting cascade expansion and recovery and other patientstorm elements.

FIG. 17 depicts historical patient storm tracking map for sepsis with anassociated event line to allow for visualization and interaction of apatient storm in the context of the event stream.

FIG. 18 depicts an ROC pattern map for a specific point in time used inassociation with a patient storm tracking visualization.

FIG. 19 depicts severity formulas used for deriving severity profiles.

FIG. 20 depicts range-based entry tables used for deriving severityprofiles.

FIG. 21 is an aggregation diagram showing how the severity profile for apatient storm cell is aggregated from all of the elements, sub-elementsand their relationships.

FIG. 22 is a block diagram of an example of a computing device that cangenerate multiple motion images of at least one clinical condition.

FIG. 23 is a process flow diagram of an example method for generatingmultiple motion images.

DETAILED DESCRIPTION SPECIFIC EMBODIMENTS

In one embodiment, the processor is programmed to provide processingsystems and methods which generate visualizations of dynamicpathophysiologic cascades of perturbation of the densities of biologicparticles and recoveries of the densities of biologic particles (andparticularly cascades of perturbations and recoveries of densities ofbiologic particles induced by sepsis), along with associated individual,relational and cascades of the forces inducing the perturbation and theforces inducing the recoveries of the densities, and for presenting thecascades of the perturbations and recoveries as well as the perturbationforces and recovery forces in a motion picture responsive to orindicative of cascades of perturbation, which may be linked to cascadesof perturbation inducing forces, which may be linked to cascades ofrecoveries, and which may be linked to cascades of recovery inducingforces.

The processing of binaries, the temporal and spatial relationships ofthe components of the binaries, the temporal and spatial relationshipsof the binaries themselves, and the temporal and spatial relationshipsof reciprocations, images, and cascades derived of linked binaries isdiscussed in detail in the aforementioned patent application and in theco-filed patent application filed Feb. 28, 2013, entitled “ProgrammaticHuman Matrix” (the entire contents of each of these applications areincorporated by reference as if completely disclosed herein).

As described in application Ser. No. 13/677,295, one visualizationformat is similar to a color radar weather map of the type commonlyviewed by most Americans on the evening news during common rain, snow,or thunderstorms, as well as during hurricanes and tornadoes. Thisprovides a dynamic visualization of a complex sepsis cascade, forexample, as a “patient storm” with the visualized patient stormdynamically spreading across the geographic space which represents thevarious systems of the human body. The term patient storm refers to apatient pathophysiologic condition, failure, or complication, such assepsis which characteristically progresses in a progressive andexpansive manner potentially involving a progressive number of systems.The storm metaphor provides the cues that can greatly shorten thelearning curve for the healthcare professional to allow them to readilysee and perceive the characteristics of the dynamic nature of anexpanding cascade of sepsis which has proven otherwise very difficultfor them to learn and understand. In one embodiment these workers seethe dynamic and relational patterns of complexity of sepsis in evolutionas they would for a major storm spreading across North America. In oneembodiment, the metaphorically presented patient storms, like weatherstorms, have patient storm components like patient storm cells, patientstorm fronts, patient storm origins, patient storm expansions, patientstorm movement, and patient storm contraction and/or recovery. Multiplepatient storms of one or more types may also be visually presented inrelation to each other. According to one embodiment, computationaltransparency is provided either automatically or upon a healthcareworker gesture (as with auditory, textual, touch, natural interfaceactions or mouse over to name a few) so that the healthcare worker canlook inside a patient storm front or a patient storm cell for example tosee which relational pathophysiologic perturbations which wereidentified or detected by the processor to generate patient stormcomponents.

According to one embodiment patient storm cells may be derived from thealpha events and the beta events of the image binaries, or the imagebinaries themselves. In the alternative, or in addition, the patientstorm cell may be derived from the beta events, alpha events, sigmaevents and tau events of the perturbation and recovery force binaries orof the force binaries, coupled binaries, quaternaries, and/or cascadesthemselves. In this way the display may generate dynamic motion imagesof the relational patient storm cell as well as dynamic motion images ofthe relational forces which induced the patient storm cells.

In the present embodiment, FIG. 1 shows an example of a Patient stormTracker and Visualization Processor (PSTVP) visualization which utilizesthe weather metaphor to present the state of a patient specificallyassociated with a patient condition—in this case sepsis. FIG. 1 is acondition-centric map for sepsis. FIG. 2 and FIG. 3 provide additionalexamples showing features which may or may not be shown on the map ormay be visible according to user preference.

The condition-centric map is made up of three layers—the background, theweather and overlays. The background is static across patients andprovides a common “geography” over which perturbation flows. The secondand third layers (weather and overlays) are both patient and timespecific. Animation shows the change in the top two layers over timeshowing perturbation data emerging, moving, growing, changing color andbeing labeled with iconic overlays creating a moving picture of thedynamic evolution of the condition in time.

The background of the condition-centric map is condition-specific. Inthe present embodiment a map is created for each condition for which thePSTVP system is monitoring. In an alternative embodiment, a single mapis used with multiple conditions. In the present embodiment, the centralelement, a circle with a star 110, is labeled with the condition 112 andrepresents the specific condition for which this map has beenconstructed. This iconic representation taps into the common metaphor ofa capital city 110. Optionally, as in FIG. 2, lines 210 radiate from thecentral element to the edge of the visualization to create triangular orroughly triangular shapes that represent the clinical spaces. Thesespaces are labeled 212 at the edge (e.g. Inflammatory, Acid/Base).Alternatively, a roughly circular area surrounds the central element andthe lines delineating clinical space proceed from this line rather thanfrom the central element itself. In the present embodiment, theradiating lines 210 are not straight but have an irregular shape tappinginto the metaphor of borders (e.g. country, state or county borders)within a weather map. In an alternative embodiment, the radiating linesare straight or smoothly curved. In FIG. 2 the irregular lines are shownand the clinical spaces are labeled 212 around the perimeter of thevisualization. In an alternative embodiment, the capital city is in theright-most position with the map extending out in a conical fashion fromleft to right. The central element 110 may be responsive to thedetection of the patterns. For example the central element 110 may beinitially missing or almost invisible, and then become visible or morevisible or otherwise highlighted when sufficient pattern components havebeen identified to warrant display of the central element 110.

In one embodiment, the background is further made up of individualcircles 120 representing sub-conditions within the central condition110. For example, as shown in FIG. 1, Blood Acidification 120 is shownas a sub-condition within the Acid/Base clinical space. These circlestap into the metaphor of cities within a weather map. Sub-conditionsmay, for example, be occurrences, relational occurrences, trends,relational trends, threshold violations, relational thresholdviolations, and a wide range of combinations of these as for exampledescribed in the aforementioned patient applications. In an exampleduring a sepsis patient storm moderate inflammation 122 may be combinedwith a fall in bicarbonate to form one sub-condition and with a fall inplatelets to form another sub-condition 124 (each which may bedesignated on the map as a circle or city). Cities, representingsub-conditions, are placed with respect to the clinical space areas. Forexample, in FIG. 2, the Hemostatic space 214 contains threecities—“Platelet Fall” 126, “Platelet Rise” 128 and “Inflammatory andPlatelet Fall” 124. Further, placement within the clinical space areamay also be chosen with respect to the relationship to other clinicalspaces and/or sub-conditions.

In one embodiment, sub-conditions are represented by pattern scriptswritten in PDL as for example described in the aforementioned patientapplications. A sub-condition may be a single pattern (e.g. PlateletFall) or a pattern made up of several other patterns (e.g. BloodAcidification). A city may be related to another city within the map.For example, Blood Acidification 120 is a classification that can beeither Buffer Depletion 130 or Acidosis 132. This opportunity forrelating cities creates an integrated relational network of patterns. Inone embodiment, the relationship between cities is shown on thebackground. In FIG. 4 the relationships between cities 410 are shown. Inone embodiment, the visibility of these relationships is toggled inresponse to a user gesture.

Cities, representing sub-conditions, are labeled 134 (as seen in FIG. 1)and are part of the background of the map and therefore are fixed inposition during presentation to the healthcare worker. The initialplacement of the cities can be determined by several factors includingstatistical correlation to the condition, disease stage, diseaseprogression, disease severity, and by relationship to region and/orother cities to name a few. However the value may be any of a number ofcorrelativity metrics relating to probability assessment. In at leastone discussion specificity is shown to provide an example of onecorrelativity metric.

The PSTVP provides a visual map editor with which an expert canconstruct a map.

The background as a whole—the central element 110, the clinical spaceborders 210 and areas 214, the cities 126 and optionally therelationship between cities 410 are displayed along with their labels toprovide a fixed geography over which perturbation flows. Familiaritywith these positions on the map helps to provide a context which can beassimilated as a whole providing rapid cognition.

The next layer of for the condition-centric map is the weather layer.This layer displays perturbation flowing over the background to tap intothe metaphor of weather flowing over a familiar geography. In thepresent embodiment, each city has a script associated with it. Withinthat script are one or more sub-scripts or statements representingpossible occurrences within the sub-condition. From these scripts, boththe scripts for the city, and all of the associated sub-scripts anassociated patient storm cell is derived. For example, the city“Moderate Inflammation” 122 (shown in FIG. 1) is defined with thefollowing PDL: identify ModInflammatorylndicator as RiseInWBC orRiseInNeutrophils or LowWBC or FalllnNeutrophils or HighWBC orHighNeutrophils or LowNeutrophils. The city “Moderate Inflammation” 122is associated with this classification “ModInflammatorylndicator.” Thismeans that ModInflammatorylndicator has seven sub-scripts eachcontaining a different pattern which the PSP system is monitoring inreal time. If any occurrences are identified within those sub-scriptsthen perturbation will be presented on the map as a patient storm cell140.

The dynamic transition of infection to inflammatory augmentation tosepsis is very a complex dynamic process. To engage complexity oneembodiment provides a multidimensional severity and progressionindicator, called a patient storm cell 140, one embodiment of which isshown 850 in detail in FIG. 8. The patient storm cell 850 is acollection of colored hexagons placed within the weather layer of theweather map, in this case a condition-centric map. In an alternativeembodiment, other visual elements are used including grey-scalehexagons, textured hexagons, pixels, other fixed or variable geographicshapes, fractals, and/or circles to name a few. In one embodiment, aseries of transformations are executed including geometric, texture andfinishing transformations to name a few. The collection of hexagons 850is determined from a metric profile of the associated city. In thecurrent embodiment, severity is used as the metric from which theprofile is created. In an alternative embodiment, other metrics are usedincluding occurrence count, statistical measures, and relational metricsto name a few. This may be used to generate an alternative weather mapwherein the relative probability of a condition is substituted forseverity (as described herein) to generate the weather movementexpansion and severity. Similarly expense may be used to generate theweather with the relative expense associated with each cascade portionand cell is substituted for severity (as described herein) to generatethe weather movement expansion and severity. The user may toggle betweenthe severity map and the probability map and the expense map, or themaps be overlaid, for example as transparencies, or otherwise integratedwith different colors, shapes, or icons, and shown together.

In the present embodiment severity is defined in terms of severitymodes. The severity modes comprise the severity of each of the differentproperties of each occurrence or relational occurrence as well asrelational modes in which properties and/or occurrences are consideredin context of other properties and/or occurrences. For example anoccurrence may be a Rise in White Blood Cells (WBC rise), properties ofthe WBC rise may, for example, comprise a WBC rise slope, WBC risemagnitude, WBC rise percent change, and WBC rise duration, WBC riseminimum value, WBC rise maximum value, WBC rise in relation to thenormal range, to name a few. Each of these properties may comprise aseverity mode for the occurrence WBC rise.

An occurrence may have a high severity by one mode (one occurrenceproperty) and a low severity by another severity mode (one occurrenceproperty). This embodiment provides the ability to define severityvariation with a high level of relational granularity across manyseverity modes applicable to each occurrence and therefore provides anoutput which more closely matches the true pathophysiologic complexity.This provides the ability to detect the subtle, insidious, and highlyvariable relational foci of progression and/or relational foci ofprogression which characterize the transition from simple infection toearly sepsis, and then from early sepsis to more severe states. In anexample a single severity mode, such as a WBC rise maximum value of 11may be of low severity but if the rise was rapid so that the WBC slopewas high (for example 0.8/hr), or if it was of high magnitude (forexample 6.4), then each of these severity modes will trigger a higherseverity in their pixels of the visualization to warn that, while theWBC is still normal, dynamic changes are in progress. Furthermore theuse of a wide range of severity modes allows more robustprotocolization. In the above example, the processor may not beprogrammed to take any action in response to a WBC of 11 but based onthe combination of a high slope and high magnitude severity may beprogrammed to order a repeat WBC in 4 hours to determine if the WBC riseis continuing. As noted previously this is one aspect of the presentembodiment provided to solve the problem of over-simplification of thecomplexity which is causing so many late detections and deaths. In oneexample a first gradation of severity used for each severity mode isdefined as an integer between 0 and 15. The profile is an array of cells860 made up of fifteen slots representing the count of severity valuesmatching the integer values. For example, a profile{0,3,0,6,0,0,0,0,0,0,0,0,0,0,0} indicates 3 instances of severity value2 and 6 instances of severity value 4 and no other severity instances.In the present embodiment, for each patient each city has a severityprofile for a given point in time within the patient stay. All of thescripts associated with a city feed into the severity profile, as shownin FIG. 21. For example, for the Moderate Inflammation city 122described above there are 7 patterns being monitored and each of thosepatterns may identify one or more instances of an occurrence of thatpattern. For example, a patient may exhibit two instances of FallInWBC,an instance of LowWBC, and an instance of LowNeutrophils. In this casethere are 3 patterns identified and 4 instances. For each of theinstances the severity of the instance can be derived. For example, thetwo instances of FallInWBC may be a severity 2 instance followed by aseverity 6 instance while the LowWBC may be a severity 4 and theLowNeutrophils may be a severity 6. In this case, given only theseverity of the instances of the sub-scripts we would derive the profile{0,1,0,1,0,2,0,0,0,0,0,0,0,0,0}. Further, individual properties of theinstances can further contribute to the severity profile. For example,the slope of the fall of the instances of the FallInWBC may beconsidered severity 7 and 3 respectively whereas the duration of theLowWBC may be considered severity 3 and the duration of theLowNeutrophils may be considered severity 4. In this case the severityprofile would now be {0,1,2,2,0,2,1,0,0,0,0,0,0,0,0}. The derivation ofseverities from properties is illustrated in FIGS. 19 through 21. FIG.19 depicts a formulaic approach in which severities for individualproperties can be derived from a formula 1920, expression or script of aDomain Specific Language (DSL) to name a few. FIG. 20 depicts anothermethod that can be used independently or in concert by specifying rangesper severity cell 2010. FIG. 21 depicts how severities are “rolled-up”into a single patient storm cell 2110. Other attributes of the scripts,the instances, the aggregation of instances, relationships of theinstances, preexisting conditions of the patient, the properties of theinstances, aspects of the aggregation (e.g. average) to name a few maycontribute to the severity profile of the city 2110 and therefore cancontribute to the size, shape, color distribution and other aspects ofthe associated patient storm cell.

As shown in FIG. 21, each severity mode translates into a severityprofile. For example, as shown in FIG. 21, the slope property of theRise In Anion Gap has a severity profile 2120. In the presentembodiment, a single property of a single occurrence of Rise In AnionGap such as the slope property would be given a single value of severity(in one embodiment, derived from a table of ranges as shown in FIG. 20).Therefore, each property of each occurrence of a pattern type (e.g. Risein Anion Gap) would have a severity mode and would provide a singleprofile value (e.g. a count of 1 in one of the 15 cells within aseverity profile). Severity profiles can be aggregated together. In thepresent embodiment, severity profiles are aggregated by adding thevalues in the respective cells. For example, a profile{0,1,0,1,0,0,0,0,0,0,0,0,0,0,0} aggregated to a profile{0,1,0,0,0,0,0,0,0,0,0,0,0,0,0} would yield{0,2,0,1,0,0,0,0,0,0,0,0,0,0,0}. All severity modes are added togetherto generate a high-level severity profile 2110 from which a patientstorm visualization can be derived. As shown in FIG. 21, each occurrencetype (e.g. Rise In Anion Gap 2130) can have several properties. Eachproperty is analyzed for severity using, in one embodiment, tables asshown in FIG. 20 or expressions as shown in FIG. 19. For each propertyof each instance (occurrence) of each occurrence type the severity iscalculated and a single-entry profile is created. All of thesesingle-entry profiles are rolled up into the occurrence type profile.Further, for each occurrence (an instance of an occurrence type) arelational severity profile 2140 is also derived (as shown in FIG. 21).The relational severity profile is calculated by evaluating one or moreseverity expressions attached to the script which defines the occurrencetype (e.g. Rise In Anion Gap). Expressions created within the occurrencescript allow for the properties of a single instance to be evaluated incontext for relational severity. Within the micro-domain of theidentified pattern relational severity can be evaluated. Within thecontext of a simple event (e.g. Rise In Anion Gap) this consistsprimarily of an evaluation of relationships between the properties ofthe event, but within the context of more complex patterns (binaries,images, etc.) the evaluation can include the comparison of properties oftwo or more occurrences which make up the overall pattern.

Occurrence types, then, as shown in FIG. 21, provide context-specificopportunities to identify relational severity. These opportunities, inthe present embodiment, are exploited by the use of severity expressionswithin the script which result in individual severity values (e.g.between 1 and 15) that are wrapped up and aggregated into severityprofiles that can participate in the general roll-up of severity asshown in FIG. 21.

In the present embodiment, the aggregation of severity profiles (asshown in FIG. 21) are additive in the sense that all severity modes arerolled up into the patient storm. Individual instances of severity arenot averaged, filtered or otherwise processed in a way in whichindividual pixels are lost.

Severity profiles provide a flexible and powerful mechanism forcapturing a complex set of severity results. The severity profile andthe patient storm visualization correspond in their ability to containand communicate pathophysiological complexity. Within a patient storm,there may be local intensity which may not dominate the overall patientstorm. An observer, using high-level weather maps can identify the localphenomenon and recognize that they may represent nascent intensity whichmay be a precursor to overall patient storm intensity or may rather betransitory and therefore anomalous. Algorithms which roll up informationinto a single value or “score” fail to accomplish this. For example, ifa “maximum” strategy is imposed then a local phenomenon will be blown upto be global and represent the present condition in a way that ismisleading. If threshold mechanisms are employed then the localphenomenon is hidden until a critical mass is attained creating thesituation in which researchers have the hopeless goal of finding “justthe right threshold” which can provide early detection withoutgenerating alarm fatigue. The severity profile has the ability tocontain a massive amount of information in a simple data structure. Theweather map as well has the ability to contain a massive amount ofinformation while simultaneously providing the ability, through the linkto a common metaphor, to provide information rapidly and evenpre-attentively about the size, direction and intensity of a complexcascade.

In the present embodiment, the severity profile data structure furthercontains the referential information to quickly identify the source ofeach pixel of severity to facilitate mechanisms of computationaltransparency.

In one embodiment of the PSTVP the severity profile is a data structurewhich contains a set of cells corresponding to severity levels 860.Additionally, the profile itself provides properties such as maximumseverity, minimum severity, perturbation volume, perturbationdistribution, perturbation spread to name a few. Maximum severityindicates the highest cell with a non-zero entry. Minimum severityindicates the lowest cell with a non-zero entry. Perturbation volume isan aggregation of all the counts in all cells. The perturbationdistribution is an expression of how counts are distributed across theset of severity levels while the perturbation spread is the number ofcells between the minimum and the maximum inclusive. These metricsfurther support the analysis and comparison of patient storms andpatient storm elements and can be accessed both instantaneously and as atime series. For example, the time series of perturbation volumeprovides an indication of the gross level of evidence of perturbationwhile the change in distribution provides a powerful characterization ofa patient storm.

In the present embodiment, the PSTVP translates the derived severityprofile of a city into an initial patient storm cell visualization. FIG.8 shows an example of this translation. The hexagon figure on the left880 is enlarged to show the detail. Each cell within the severityprofile is assigned a color. The count within the cell translates to thenumber of hexagons used. The cell severity value determines the color ofthose hexagons. In one embodiment a multiplier is used such that thenumber of hexagons is increased in a proportional manner from theinitial counts. In one embodiment the hexagons are placed starting withthe most severe in the center and then moving in a spiral fashionoutward 880. The severity-centric display emphasizes the metaphor of apatient storm cell. In one embodiment the cells in the severity profilerepresent rings in a circle and the count within the cell determines orroughly determines the width of the ring. In one embodiment, groups ofhexagons 910, as depicted in FIG. 9 are used. In the present embodimentthe patient storm cell directly derived from the severity profile doesnot represent the final visual representation on the weather layer ofthe condition-centric map. The patient storm cell visual is the initialrepresentation that will be altered by other conditions within the mapbefore being rendered within the weather layer.

In the present embodiment, once the initial representation of thepatient storm cell has been completed several other steps are takenbefore the cell is rendered on the weather layer. Those steps includemove, distort, merge and finish. In an alternative embodiment othermeans to modify the patient storm cells to improve visualization may beused.

Patient storm cells represent a level of perturbation within a clinicalspace. The region associated with the clinical space can have manypatient storm cells presented. If a city has any perturbation (asrepresented by a number>0 in a cell of a severity profile) an associatedpatient storm cell will be placed on the map. The location of a patientstorm cell is the result of multiple factors. A patient storm celllocation is first determined on the basis of the city itself but then isaltered by the “pull” of related cities on the map. In the presentembodiment, the initial placement on the map is determined by thelocation of the city, a vector between the city and the central element110 (e.g. Sepsis) and a circle around each city 1020 called the limitperimeter. Each city has a limit perimeter which is defined as a circlearound the city with a specified radius. These limit perimeters areshown in FIG. 10. In one embodiment the limit radii are equal for allcities. In alternate embodiments, the radii are different for some ofthe cities, or for each city. The initial location of the patient stormcell is selected as the point of intersection between a vector drawnfrom the center of the central element through the center of the cityand bisecting the limit perimeter at the farthest point of the perimeteraway from the central element. This point identifies the initial pointof the patient storm cell. If no other alterations were applied, thenthe patient storm cell would be placed by putting the center point ofthe patient storm cell visualization on this initial point.

In the present embodiment, once the initial point is established, forcesare applied to reposition the patient storm cell according to relatedcities on the map. In the present embodiment, the PSTVP includes aphysics engine which models forces on the map. In this way, cities pullpatient storm cells of the cities to which they are related with a forceproportional 1030 to the severity profile derived of the associatedcity. For example, for a given city once an initial patient storm celllocation point is determined then the PSTVP identifies all of the citiesthat are related to the city are identified. For each related city apull force 1030 is determined by the “weight” of the associated severityprofile. The direction of this pull force is determined as the directionof a line starting at the current city drawn to the related city (asshown on FIG. 10). The potential location of the patient storm cell isthen calculated by aggregating the forces applied (and setting aspecified constant simulated value for time). Finally the perimeterlimit is applied to limit the location of the center. In other words, ifthe potential location is located outside of the limit perimeter thenthe final location is determined as the point where a line between theinitial point and the potential point bisects the limit perimeter. Thispoint then becomes the central point of the patient storm cell. In onealternative embodiment there is no limit perimeter. In one alternativeembodiment the combination of the severity profiles between the currentcity and the related city is used to determine the force. In onealternative embodiment the central element 110 applies a minimum forceregardless of whether the script associated with the central element hasa non-zero severity profile. In one embodiment, the physics engine istuned per condition to alter the way that elements are moved, distortedand/or merged specifically for the target condition (e.g. Sepsis orCHF).

Once the final location is determined for the patient storm cell thenfurther alterations are applied. These alterations may include residualvisualization, force distortion and patient storm cell merge to name afew. Residual visualization is the process of providing a visual“residue” of the patient storm path as determined by the forces whichapply. In the present embodiment, a residue area is determined bycalculating the location of the patient storm cell from the initiallocation to the final location with a given time granularity of thetransition. For example if the granularity were determined to be 10 thenthe patient storm cell would be set at the initial location and then 8locations between the initial location and the final location and thenfinally the final location. A perimeter can then be determined aroundall of these patient storm cells to create the residue area. Within theresidue area a visualization of severity is placed by using the minimumseverity and a coverage value determining how completely to fill in theresidual area. In an alternative embodiment other severities areincluded. In an alternative embodiment the residual is created bycombining the patient storm cell visualizations along their path fromthe initial to the final location. The residual visualization streamsbehind the patient storm cell visualization to form a singlevisualization.

In the present embodiment, force distortion is also applied to thepatient storm cell visualization. The forces, as described above, areapplied to the initial patient storm cell shape to generate adistortion. In one embodiment the distortion is created by aggregatingthe forces and “pulling” the patient storm cell shape as if it were anelastic enclosure around fluid. In one embodiment this “pulling” is doneat each of the angles at which the relational force is applied. In thepresent embodiment the distorted shape is then used to generate thepatient storm cell. In an alternative embodiment, the forces pullindividual hexagons away from the patient storm cell creating aseparation from the patient storm cell. Each individual hexagon ispulled in relation to its distance to the related city. In this way edgehexagons are pulled farther (given that the physics engine may model oneor more aspects of gravity and so the hexagons may be affected bydistance as well as mass) than the interior hexagons causing ascattering toward the related cities. In one embodiment the city (i.e.the location of the city) is given a “gravity” force to instigatefurther distortion. In one embodiment, the initial location of thepatient storm is given a “gravity” force to instigate furtherdistortion. Distortion determines a skeleton of the overall shape of thepatient storm cell (or combined cells) into which color elements areplaced to create the patient storm cell visualization.

In one embodiment an area of the map (or the entire map) is used todetermine the placement of color in association with a patient stormcell using probability of placement. In this model each location canreceive a pixel, hexagon, colored shape or icon to name a few and eachlocation is assigned a probability based on a number of factorsincluding the distance from the associated city, pathways of influencebased on related cities, variability of the severity profile to name afew. Once probabilities are assigned then individual visual elements(e.g. pixels) generated by the associated severity profile are scatteredinto the probabilistic matrix to determine their location.

In the present embodiment, a proximity threshold between patient stormcells can be breeched to instigate a patient storm cell merge. In analternative embodiment, the triggering of a merge may be based solely ona comparison of the severity profiles of related cities rather thanproximity on the map or may be based on at least a combination ofseverity and proximity. Several different forms of merge can occur. Thecomplete merge can be triggered in which the profiles of the mergingpatient storm cells are simply added together to create a single patientstorm cell. Alternatively, patient storm cell merging allows the centersof the patient storms (e.g. the high-severity areas) to remain distinctwhile the rings of lower severity merge into a single element. Theserings around multiple patient storm centers then form a shape similar tomerged circles. In one embodiment the outside rings maintain the shapeof a single patient storm cell while only the interior area displaysmultiple centers creating a multi-centered patient storm cell. Anynumber of patient storm centers may be included into a single patientstorm system.

In one embodiment, the move, residual, distortion and merging are donein a way to restrict any of the patient storm cell visualizations to beon top of cities for which there are no severities found.

In one embodiment, the shape skeleton created by residual, distortionand merging become the basis for the general outline of the patientstorm cell and additional transforms are applied to remove certainelements of geometric precision and symmetry such that a moreweather-like appearance is generate while maintaining the overall shapeand proportion of severity.

In the present embodiment, a finish stage is executed to smooth,texture, visually enhance to name a few.

In one embodiment, the stages of transformation are shown to a user orfor the purpose of facilitating map creating and/or modification. FIG.11 depicts a wireframe display used to show the stage after move,distort and merge but before the colorization and finishing process hasbeen completed. Cycling through the stages of transformation provides aninformative visualization of the way the data is translated from rawinput into the weather display. Further, healthcare workers can use thevarious stages to review the data. For example, reviewing the datawithout the application of the physics engine would allow the user tosee the exact profiles associated with each sub-condition on the mapwithout respect to relationships to other sub-conditions or merginggenerated by proximity. Monitors could be set to show a particular stageof the transformation or a trellis display showing multiple stagessimultaneously can be employed allowing the full impact of the weathermetaphor to be employed alongside less transformed visualizations.

The PSTVP applies the above techniques for all cities on thecondition-centric map to generate the weather layer of thevisualization. In the present embodiment the weather layer only usesdata for a specified time window.

In one embodiment shapes (such as hexagons, squares, rectangles, to namea few) which completely cover the background of the map make up theweather layer. In this embodiment, one or more severity modes areassociated with a single cell on the map and determine the color of thatcell. In this embodiment, no movement, distortion, merging or finishingis done, but the patient storm visualization emerges from cells becomingactive and changing in color over time. The cells may be positioned inrelation to each other so that specific conditions such as sepsis willappear similar to weather. In particular cells responsive to singleperturbations and milder perturbations may be positioned to the left andor above cells responsive to relational perturbations or more severperturbations so that the patient storm expands and/or moves to theright or downward as the sepsis progresses even though the actual cellsmay not move.

In one embodiment the display is comprised of density cells which aregraphical encapsulations of a perturbation. Each density cell containsmathematical or other information related to the density perturbation itembodies. A density cell may reside in predetermined locations in eachclinical region of the geographic space. Density cells are alsodesignated (and positioned on the graphical space) by the biologiccompartment in which they reside, and the particle itself. Density cellsmay also be designated and positioned on the graphical space by theirpolarity since perturbations of different polarity of the same densityparticle generally occurs by different forces and therefore oftenrepresent completely different biologic events.

An example of a positive density cell may be a square comprised of 10 ormore density cell compartments called “density organelles” or simply“organelles.” Each organelle contains a single mathematical or otherdensity value related to the perturbation which defines the cell. Thedensity value can include for example an; absolute magnitude, absolutevalue, duration, slope, area under the curve (or over the curve in theevent of negative polarity), acceleration, the product of the absolutemagnitude and the square of the slope, the personal threshold specifiedrelative to the personal range, the population threshold relative to thepopulation range, a testing trigger threshold, a treatment triggerthreshold, a preferred threshold and/or other value.

A mathematical number for each of the above values may be provided ineach organelle wherein the value is known or can be calculated. Thisproduces a matrix of mathematical values which relate to theperturbations of densities over specific time intervals. The values canbe designated with colors which relate to the severity of theperturbation so that the organelles have both a color and a mathematicalvalue. Although density cells are a common cell type, other cell types,which, for example, relate to particle size or other features, may beprovided.

Density cells may contain mathematical information related to a densityperturbation of a single particle or they may be “relational densitycells” which relate to a relational perturbation of a plurality ofparticles. Additional organelles may be added to accommodate the manypotential values related to organelles defining. Each time a new datapoint is added to the time series matrix at least one new density cellis generated and positioned on the display in the specified location forthat cell. As with the earlier discussed weather maps, time may be shownalong an x axis (or other axis) with the cells being in fixed positionsalong the Y axis but moving with time to the left as new cells aregenerated at that site. Alternatively, each cell is replaced as timeproceeds (with the cells fixed in place in 2 dimensional space). A 3dimensional representation with fixed cells and time along the thirdaxis may be shown which can then be sectioned perpendicular to the timeaxis to view the pattern at any specific time or parallel to the timeaxis to view density relationships over a time period. The image may beprovided in transparency so the user can look into the image, forexample in a perspective view, and see the relationships of the past orfuture (which may be projected) perturbations inside, beyond the timedefining the surface of the image. In this way a 3 dimensional (forexample) rectangular matrix of mathematical values and severity colorsis generated which comprises the global mathematical image and coloredimage of the densities and perturbations of an individual over time.Portions of these images may be converted to more typical weather radarlooking images when clinical failures are identified.

The top layer for the condition-centric map is the overlay layer. Theoverlay layer provides iconic annotation and an indication of relevantevents, trends or other elements to be highlighted. As an example, theoverlay layer will display patterns of perturbation 320 and recovery310, rapid increases or decreases in severity, condition identification,areas of missing data, areas of data coming in with an entry delayoutside of prescribed protocol, treatment/intervention events, expectedrecovery indicators, patient storm path, and or patient storm trajectoryindicators to name a few.

In the present embodiment, the overlay layer uses icons that tap intothe weather metaphor. For example, as shown in FIG. 3, trends inperturbation 320 and recovery 310 are displayed in a similar way thathigh and low pressure fronts are displayed on a weather map. An iconicrepresentation within the clinical space—P for perturbation, R forrecovery is displayed. Further bands 330 are shown to provide thedirection and size and relative location of the trend. For example, asshown in FIG. 3 the Hemostatic space is recovering or has recentlyrecovered and therefore displays an R 310 and an iconic band 330 showingthe space moving away from perturbation. On the other hand, theAcid/Base space is displaying a great increase in the amount andseverity of perturbation and therefore is shown with a P 320 and a largeband 350 close in to the center and with arrows showing a continuedtrend toward additional perturbation. In this way the overall state andtrend of the clinical spaces can be rapidly assimilated. In oneembodiment, lightning icons are used to delineate rapid increases inseverity. In one embodiment, grey shapes are used to indicate missingdata. In one embodiment, arrows are used to indicate patient stormdirection. In one embodiment, a band of color is used to indicate aprobabilistically derived patient storm path. In one embodiment, linesare used to connect treatment events with related (or possibly related)severity elements. In one embodiment, the background of a clinical spaceis colored to indicate perturbation or other states and/or trends.

In one embodiment, several overlay layers are possible with a specificfocus and can be toggled on and off independently. For example, oneoverlay layer may be specific to the relationship between treatment andperturbation while another layer may be specific to highlightingmissing, sparse or delayed data and another layer may be specific toperturbation and/or recovery forces. These layers could be turned on oroff and could be used in conjunction depending on the needs and focus ofthe user.

In the present embodiment, time is used to animate the condition-centricweather map to produce a moving picture of systemic weather over theuniverse of clinical spaces, sub-conditions and the target condition.The PSTVP receives a set of severity profiles for a given point in timeto produce visualizations on the weather layer and analyzes the currentset along with the past sets to generate the overlays on the overlaylayer. As the data changes in time those changes are reflected withinthe weather and overlay layers. Moving through time in successionprovides an animation showing the evolution of perturbation. Time can beshown forwards and backwards at various speeds. A time loop is providedto show recent evolution or evolution within a specified area of time.

In the present embodiment, the PSTVP provides several different types ofinteraction with the condition-centric weather map. Gestures with amouse or a touch environment or a natural interface can be employed tonavigate, drill down, zoom and scroll to name a few. In the presentembodiment, the user may annotate visually or with audiovisual notes.

In one embodiment the condition-centric weather map may be manipulatedby the healthcare worker and/or researcher to consider hypotheticalscenarios or scenarios based on the rejection of certain test results orevents which may be considered in error, anomalous or otherwiseinaccurate. Alternate visualizations (along with their updated, added orannotated data) may be stored in whole and may be compared against theworking set to understand the results of the altered data.

The PSTVP presents maps, such as the map in FIG. 1, both individuallyand in combination in a trellis display. For example, a single patientcan be shown with a 4×4 trellis display of sixteen maps each displayingthe state with regard to a different condition such as sepsis,congestive heart failure, hepatic failure, renal failure, drug ortransfusion reaction to name a few. This display is typically sortedwith the most severe first providing a rapid review of the state of thepatient with reference to the conditions monitored.

Alternatively, the PSTVP presents a set of patients for a singlecondition (e.g. Sepsis) in a trellis display. Sorts are provided tohighlight patients with the greatest severity and or correlativitytowards the selected condition. Filters can be provided by weatherelements including minimum severity within clinical spaces, patientstorm types, initiating clinical space, dominant clinical space, overallperturbation coverage (i.e. global perturbation volume), perturbationand/or recovery trends, recent changes, recent events associated withchanges, incomplete force binaries to name a few.

In one embodiment, the condition-centric weather map is presentedalongside other visualizations including time-series display, labrecords, physician notes, ROC charts, patient event logs to name a few.Further, interaction with the weather map can be used to highlight,select, sort, filter or otherwise manipulate related visualizations. Forexample, the selection of a weather cell within a map can select all ofthe points within a time series display which contributed severity intothe selected patient storm cell and can induce a display of the timeseries, tabular or sequential values, and or time series relationshipsto provide computational transparency. Alternatively, selections ofpoints within a time series display can zoom, scroll and/or highlightthe weather map as well as move the weather map, or a set of weathermaps, to a specific time.

A health worker may want to see the evolution of a patient conditionwithin the clinical spaces in a glance along with a detailedvisualization of the state at a particular point in time. In oneembodiment, the condition-centric weather map is placed alongside ahistorical weather map in which time the element on the x-axis asdescribed in U.S. patent application Ser. No. 13/677,295 filed Nov. 14,2012. Animation within the condition-centric weather map can beassociated with a single vertical line within the historical weather mapand arrows, highlights, iconic elements or other visual cues can be usedto tie these two together such that the evolution in time is presentedwithin the historical weather map and an animation of the state overtime is presented in the condition-centric weather map.

In one embodiment in place of or in conjunction with thecondition-centric patient storm tracker visualization the visualizationin FIG. 6 is shown. In this patient storm tracker map clinical spacesspan from left to right and are stacked within the visualization. Citiesare placed in a similar fashion as described above and may be alwaysvisible or may appear if the patient storm warrants their appearance (asby generation the storm cells which relate to the city). In thisvisualization, patient storm patterns 610 may grow or move fromleft-to-right as, for example, severity, correlativity to a conditionand/or relational complexity. FIG. 6 depicts a patient exhibiting apattern and/or symptoms of new onset acidosis 620 which can indicateoccult or overt hemodynamic insufficiency. The lack of active moderateor severe patient storm cells in the regions of inflammation 630suggests that it is not likely that this is a sepsis patient storm.

In one embodiment in place of or in conjunction with thecondition-centric patient storm tracker visualization the visualizationin FIG. 12 is shown. FIG. 12 depicts a historical patient storm trackermap. In this visualization, time is shown on the x-axis and in this waythe evolution of a condition can be accessed at a glance. The historicalpatient storm tracker map is described in the aforementioned patientapplications. FIG. 14 depicts the severity-centric version of this mapwith a patient which displays a rapid expansion of perturbation 1280followed by a period of recovery 1338. FIG. 16 shows how overlays withinthis map can be used on top of the historical patient storm tracker map.The historical patient storm tracker map can be used as a navigationmechanism for the condition-centric patient storm tracker and othertime-animated maps for example providing a histogram-style navigationslider.

FIG. 17 depicts one embodiment in which an event bar 1710 accompaniesthe historical patient storm tracker. These both can provide a usefulnavigation tool for the condition-centric patient storm tracker andother time-animated maps. In this way the location of patientevents—surgery, drug therapy, diagnosis to name a few—can be analyzed inthe context of perturbation within clinical space in time (as per thehistorical patient storm tracker) as well as an animated point-in-timedisplay of the condition-centric and/or related maps. Gestures withineach visualization—the condition-centric map, the historical map and theevent bar 1710 can be captured to indicate user intent with regard tozoom, time-navigation, filtering, drill-down, sorting to name a few.

In one embodiment in place of or in conjunction with thecondition-centric patient storm tracker visualization the visualizationin FIG. 18 is shown. FIG. 18 shows an ROC pattern chart depicting thecurrently identified patterns in ROC space for a given point in time ortime span. The ROC pattern chart provides rapid access tosensitivity/specificity towards a condition (e.g. sepsis) insubstantially all patterns being monitored. Each pattern for whichoccurrences are identified will be displayed in the location 1820 whichindicates sensitivity and specificity derived from a training set ofretrospective patients or supplied by a third party or derived fromreal-time patients to name a few. In one embodiment, as shown in FIG.18, the pattern dots 1820 are colored using the maximum severity withinthe severity profile for the given pattern. In one embodimentrelationships are depicted using arrows. In one embodiment, theselection of individual or sets of patterns are used to affect othervisualizations such as filter, sort and/or highlight to name a few.

In one embodiment potential future trajectories and paths of the patientstorm are projected on the visualizer. One method for projecting a pathmay be to project the slope of the expansion of the cascade image andproject that slope outwardly. Another method of projecting thetrajectory comprises identifying the pattern (such as a sepsis pattern)and then projecting the values of a plurality of parameters whichcomprise the pattern to points at future time intervals which areconsistent with progression of the condition over the time intervals.For example the slope of the platelet fall, the bicarbonate fall, and/orthe band rise may be determined then each projected forward (for examplethe slopes may be projected for 2-24 hours or more) and the relationalpatterns of these values may be determined to predict a potentialtrajectory (which may for example be a “worse case” trajectory) subconditions. In an alternative, slopes (which may be “worst or near worstcase” slopes) which occur in certain conditions (such as sepsis) knownby experience, determined by review for retrospective data sets or inprospective trials may be used to enhance the accuracy of theprojections. For example, through experience with many advanced sepsiscases one of the present inventors has noted that until the septic stateis controlled, the bicarbonate may fall with a slope of about 1meq/hour. This will induce an attendant increase in respiratory drivewhich can be projected as it will be rise as a direct function of thefall in bicarbonate. Heart rate can also be expected to rise in responseto the rise in respiratory rate and fall in bicarbonate. It is notnecessary to precisely predict these values and the relationalsub-conditions but rather to simply project a path which is consistentwith one possible path if the pattern progresses without intervention.From the perspective of the visualizer the bicarbonate may exert agravitational effect on the respiratory rate and heart rate increasingthe severity of any specific value of these parameters. The projectedpath (which can be defined by the processor, and then presented to thehealthcare worker for example by query or automatically) provides awarning to healthcare workers that time is of the essence and rapidintervention or at least frequent follow-up is required to determine ifthe patient will follow such a path.

Alternatively, a trellis display of possible “futures” may be presentedto the healthcare worker each with an indication of the conditions thatwould cause the proposed future.

In one embodiment probabilities are attached to the futures and/or pathdisplays.

One approach for projecting a path and for determine a patient specificfrequency of automatically ordered lab testing is to calculate apotential worst case path or value of a parameter and then identify theretesting time based on the minimum change of the parameter which wouldhave clinical relevance given the potential condition or conditionsidentified by the processor. For example, if the processor hasidentified severe sepsis as a potential condition, then a projectedbicarbonate (or other lab values) can be calculated by Equation 1:V _(p) =V _(s) +T _(D)(dV/t)+T _(i)(dV/t)  Eq(1)

Where:

-   -   V_(p) is the projected value of the parameter at the projected        time;    -   T_(i) is the time interval between the last sampling time and        the projected time;    -   T_(D) is the delay between the sampling time and the display        time;    -   V_(s) is the value of the parameter at the sampling time (this        may not be known until later if there is a transport and/or        testing delay); and    -   _(d)V/t is the worst case or near worst case slope of the        parameter given the condition(s) identified as potentially        present by the processor (such as sepsis).

An efficient timing of retesting which would enhances the ability toearly detect significant change may be made by setting the next samplingtime to an interval calculated from specifying the minimum or maximum(depending on the polarity of the trajectory) of the projected valuewhich would (if known) affect diagnostic or therapeutic action given thecondition(s) identified as potentially present by the processor. Forexample, suppose the bicarbonate value at the sampling time (Vs) was 20and is identified by the processor as falling at a rate of 0.5 meq/hourand the processor further identified the image as representing a highprobability that sepsis is present, yet the processor identifies thenext test for bicarbonate has been ordered by the physician at 8 hoursand the average, worst 10 percentile (or other measure), of delay fromsampling time to display time (TD) is known or calculated to be 1 hourfor this particular hospital ward. Then in one embodiment, the processorcan be programmed to identify an improved sampling interval based on aprojected “worst case” bicarbonate fall of 1 meq/hour for the conditionof sepsis, and adjust the repeat bicarbonate testing to 2 hours since afall in bicarbonate to 17 (the value which could reasonably be presentin 3 hours (sampling interval plus delay interval) would (if known)affect diagnostic or therapeutic action given the condition(s)identified as potentially present by the processor (in this casesepsis). In the alternative, when managing this patient without theprocessor intervention of the present embodiment the bicarbonate couldhave fallen to 11 (before outputted as 12 on the display) and this valuein this range can result in death (perhaps before the sample is eventaken). As demonstrated in this example, the condition or patternspecific projection of individual parameter values provides both warningand a means to improve sampling time and therefore the diagnosticutility of the motion image and improved protocolization of treatment.Furthermore the projection of multiple parameters can be used to renderone or more possible paths which the patient storm may take if, forexample, intervention in not provided.

In an embodiment, a display is provided indicative of a time matrixcomprised of solved perturbation image binaries, recovery imagebinaries, perturbation force binaries, and recovery force binaries, aswell as unsolved binaries as described in co-filed application U.S.Provisional Patent Application Ser. No. 61/770,971, filed Feb. 28, 2013,entitled “Programmatic Human Matrix” (the entire contents of which isincorporated by reference herein for all purposes). Binaries and/or thegraphical representations derived from them (such as weather map typeimages) may have a different colors, or other markings to differentiatedifferent binaries and between solved and unsolved binaries or the stormcells associated with different binaries.

In one embodiment, the healthcare worker may choose to visualize apatient's weather map as derived from solved and/or unsolvedperturbation image binaries, recovery image binaries, perturbation forcebinaries, and/or recovery force. Drill downs requesting the binaryinformation relating to the patient storm cells may reveal the spatialand temporal pattern relationships of both density modifying forces anddensity changes. Drill downs requesting the image binary informationrelating to the patient storm cells may reveal the spatial and temporalpattern relationships of events, patterns and cascades comprising theimage of a patient's condition and care.

Other weather metaphors which may be generated to visualize sepsis orother conditions include, for example tornadoes and hurricanes. Othernon-weather metaphors include forest fires, floods,battles/battlefields, ocean currents, population growth or movement,traffic movement, to name a few.

In one embodiment, used independently or in concert with thecondition-centric weather map, a 3-dimensional globe is portrayed withinthe visualization indicating sections which are displayed by individualcondition-centric maps. In this way, an array of conditions is monitoredand portrayed in three dimensions as sections on the surface of a“globe”. The health-care worker can interact with the 3-dimensionalpatient globe such that it can be spun, “pushed back”, “brought forward”to name a few associated with gestures indicated through a mouse, touchsurface, natural interface to name a few. In one embodiment, sections onthe globe represent individual conditional-centric maps. The user maythen spin the globe seeing, at a glance, storms represented for eachcondition being monitored on the surface of the globe. In oneembodiment, the location of the sections on the globe is fixed torepresent a global geography such that a user can remember the locationof individual maps. The user may then select one or more sections toshow side-by-side with the patient condition globe. The side-by-sidedisplay may be a single map or a trellis display with selected mapsindicated by color, letter, number or some other symbolic and/or iconicmnemonic to associate with a highlighted section on the patient globe.In one embodiment the trellis associated with the patient globe isautomatically (or be default) filled with the most severe stormsidentified for the conditions monitored. The individual storm maps aresorted by maximum severity, perturbation volume or other stormclassification.

In one embodiment, used independently or in concert with thecondition-centric weather map, a 3-dimensional translucent globe isportrayed. In this way, an array of conditions is monitored andportrayed in three dimensions as planes that pass through the center ofthe transparent or translucent globe. Each clinical system is a circularplane passing through the center globe. In this way, all clinicalsystems intersect in the center so that relational patterns betweensystems may expand across the center into any other system. Storm cellsmay be 3-dimensional objects which have height, width and depth. Thehealth-care worker can interact with the 3-dimensional translucentpatient globe such that it can be spun, “pushed back”, “brought forward”as well as entered into in 3-dimensional space to name a few associatedwith gestures indicated through a mouse, touch surface, naturalinterface to name a few. The severity of the affected densities andparameters in a system may determine its shape, size and position in thecircle relating to that system with more severe perturbation being morecentrally located and very severe being at the center itself. Since verysevere perturbations generally affect multiple densities from multiplesystems severe cascading conditions such as sepsis will demonstrate alarge central mass of color storm cells with severe colors such aspurple or red, in the center and the milder colors such as green in theouter portions of the mass. In one example, the time lapsed animationthe storm cells move and/or expand, grow, and emerge centripetally withearly outer green and then later centrally located purple and red insidea 3D storm mass at the center of the sphere. The planes may be rotatedto show the intersection and the storm expanding across the center (attimes in both directions) into other adjoining plane. In one embodimentthe planes within the translucent globe interact with each other. In oneembodiment the interaction is through a global physics engine that pullsstorm cells in 3 dimensions both from related storm cells within thesame plane and by related storm cells on other planes within thetranslucent globe. In one embodiment, the 3-dimensional location of theplanes within the globe is fixed to represent a global topography suchthat a user can remember the location of individual maps. In oneembodiment the user can select individual planes within the globe to seethem side-by-side with the translucent globe. In this way a3-dimensional weather-map is shown in which storm cells are not simplyrepresented as 2-dimensional but as 3-dimensional shapes projected usingrendering that provides the visualization of 3-dimensional objects on a2-dimensional display system. The user may select one or more planes toshow side-by-side with the globe. The side-by-side display may be asingle plane or a trellis display with selected planes indicated bycolor, letter, number or some other symbolic and/or iconic mnemonic toassociate with a highlighted plane within the patient globe. In oneembodiment the trellis associated with the translucent patient globe isautomatically (or be default) filled with the most severe stormsidentified for the conditions monitored. The individual storm planes aresorted by maximum severity, perturbation volume or other stormclassification.

In one embodiment, used independently or in concert with thecondition-centric weather map, the map is made up of a circular linealong with cities, as described above, are placed. The background is,therefore, a fixed circle with cities arranged along the line. Theweather layer is then layered on top of this set of cities withperturbation, as described above, shown as expanding color, shapes ofcolor (e.g. hexagons), sets of icons to name a few. In one embodimentmovement of storm cells associated with a city toward the center of themap is proportional to perturbation volume increases. In one embodimentthe movement and/or expansion is proportional to the sum of theperturbation volume between related cities and the direction of theexpansion is determined by a vector drawn between the cities to eachother across the map.

In one embodiment the map is circular which regions radiating from thecenter or a center circle or other shape. A region for mild storm cellsand or single events indicators is positioned around the perimeter. Asthe condition becomes more sever the regions move closer to centergenerate color indications, as severity worsens further this entersthese color indications reach the center and may extend into the regionswhich are relationally affected.

One embodiment comprises a patient monitoring system having at least oneprocessor programmed to generate an image which displays a patientcondition as color weather radar on a map. The map can be a 3D map or 2Dmap with or without a time axis. The map may be rectangular, circular,or spherical. The map may be divided into sections that representclinically differentiated subsystems. The sections may intersect and thesections and/or the intersections may be movable or fixed. The positionof the sections in relation to each other may be responsive to thepattern detected by the processor or other factors such as recentprocedures or medication. The map may have different configurations,different cities, and or different spatial relationships of the sectionsresponsive to the dynamic clinical pattern or image detected by theprocessor.

The positions of the sections and/or cites may be dynamic responsive tothe pattern or image detected by the processor so that for examplesections most affected are moved or displayed in relation to each otherto better display the pattern relationships. The map may have multipleplanes projecting through a center intersection. At least one monitoredcondition may be positioned one the map so that the weather imageexpands, develops or moves over the condition the monitored conditionmay be represented as at least one capital city which may be fixed. Inone embodiment monitored sub-conditions are represented as cities on amap which may be fixed. The borders may be shown between the clinicallydifferentiated subsystems as straight lines, curved lines, or anotherpattern of lines or border indications. The borders may be configured tolook similar to borders as between states or counties. The map may bedivided into roughly triangular sections which all intersect the centeror intersect a center space such as a central circle. A state or subsetof the state of the patient or a condition for a single point in timemay be shown. The pattern of perturbation inducing forces,perturbations, recovery inducing forces, and recoveries, and orrecoveries associated with a condition monitored may be show as a stormcell over, adjacent or proximate to the location associated with thatcondition. The perturbation associated with a sub-condition may be shownas a storm cell over, adjacent or proximate to a location associatedwith that sub condition. The objects, data, time series, and datapatterns which relate to a cell may be displayed at the same time as thecell or in relation to the cell as by touching, or otherwise selecting acell.

One embodiment comprises a patient monitoring system for generatingdynamic visualizations of clinical conditions comprising a processorprogrammed to, generate images responsive to a clinical condition on andisplay having clinical regions which intersect, generate at least onediagnostic region positioned on the display adjacent the intersection ofthe clinical regions for identifying a clinical condition, andincrementally migrate or expand the image toward the diagnostic region,in response to detection of values or trends suggestive of the presenceof the clinical condition, and generate images responsive to a clinicalcondition on an display having clinical regions which intersect. Theprocessor may generate cells of images responsive to a clinicalcondition on the display map and migrate, expand, or add new cells in adirection toward the diagnostic region, in response to detection ofvalues or trends suggestive of the presence of the clinical condition.The possessor may generate cells of images comprising or responsive toperturbations of biologic particle densities wherein the cell iscomprised of a plurality of organelles responsive to features of theperturbation. The cell may be comprised of a plurality of organelleswherein different organelles are responsive to different features of theperturbation, the features comprising at least a plurality of peakvalue, slope, magnitude, or percent change.

One embodiment comprises a processor programmed to generate cells ofimages responsive to a clinical condition on an display map havingclinical regions which intersect, generate at least one diagnosticregion positioned on the display map adjacent the intersection of theclinical regions for identifying a clinical condition, incrementallymigrate, expand, or add new cells in a direction toward the diagnosticregion, in response to detection of values or trends suggestive of thepresence of the clinical condition. The cells may be responsive toperturbations of biologic particle densities wherein different cells areresponsive to different features of the perturbation, the featurescomprising at least a plurality of peak value, slope, magnitude, orpercent change, the processor may aggregate the cells on the map withinthe specific areas of clinical regions to which the perturbations of thecells corresponds, and may migrate, expand and/or emerge new the cellswithin the regions overtime in response to changes in the perturbations,the cells providing a unifying motion image on the display mapresponsive to the aggregate dynamic variations of the perturbations. Theprocessor may generate a display map having clinical regions withspecific areas for specific perturbations so that the dynamic image isdirectly indicative of the actual dynamic patterns of perturbations andmay itself be imaged by the processor or another processor for analysis.

One embodiment comprises a patient monitoring system for generatingdynamic visualizations of clinical conditions comprising a processorprogrammed to detect perturbations, generate a display map havingclinical regions and markers relating to perturbations, combinations ofperturbations, or clinical conditions within the regions, generatedynamic images responsive to the perturbations wherein the dynamicimages appear and move in response to variations in the perturbationsand in response to new perturbations, in a manner similar to colorweather radar over the display map and the markers. The processor mayfurther detect clinical conditions by analyzing the perturbations,project the potential direction of the movement based on the pattern ofperturbations, and output an indication on the display of the expecteddirection of movement of the clinical conditions in spatial relation tothe dynamic images.

The Appendix includes one embodiment of a domain specific languagescript relating to detection and imaging of inflammation, acidosis, aparenteral antibiotic indicating disorder (PAID), pathophysiologicdecoherence or divergence (PD), physiologic coherence (or convergence)CONV, systemic inflammatory response syndrome (SIRS) (which is moreadvanced than the conventional SIRS definition) and varying degrees ofsepsis severity, and other conditions.

FIG. 22 is a block diagram of an example of a computing device that cangenerate multiple motion images of at least one clinical condition. Thecomputing device 2200 may be, for example, a mobile phone, laptopcomputer, desktop computer, or tablet computer, among others. Thecomputing device 2200 may include a processor 2202 that is adapted toexecute stored instructions, as well as a memory device 2204 that storesinstructions that are executable by the processor 2202. The processor2202 can be a single core processor, a multi-core processor, a computingcluster, or any number of other configurations. The memory device 2204can include random access memory, read only memory, flash memory, or anyother suitable memory systems. The instructions that are executed by theprocessor 2202 may be used to implement a method that can generatemultiple motion images of at least one clinical condition.

The processor 2202 may also be linked through the system interconnect2206 (e.g., PCI®, PCI-Express®, HyperTransport®, NuBus, etc.) to adisplay interface 2208 adapted to connect the computing device 2200 to adisplay device 2210. The display device 2210 may include a displayscreen that is a built-in component of the computing device 2200. Thedisplay device 2210 may also include a computer monitor, television, orprojector, among others, that is externally connected to the computingdevice 2200. In addition, a network interface controller (also referredto herein as a NIC) 2212 may be adapted to connect the computing device2200 through the system interconnect 2206 to a network (not depicted).The network (not depicted) may be a cellular network, a radio network, awide area network (WAN), a local area network (LAN), or the Internet,among others.

The processor 2202 may be connected through a system interconnect 2206to an input/output (I/O) device interface 2214 adapted to connect thecomputing device 2200 to one or more I/O devices 2216. The I/O devices2216 may include, for example, a keyboard and a pointing device, whereinthe pointing device may include a touchpad or a touchscreen, amongothers. The I/O devices 2216 may be built-in components of the computingdevice 2200, or may be devices that are externally connected to thecomputing device 2200.

In some embodiments, the processor 2202 may also be linked through thesystem interconnect 2206 to a storage device 2218 that can include ahard drive, an optical drive, a USB flash drive, an array of drives, orany combinations thereof. In some embodiments, the storage device 2218can include a multiple motion image module 2220. The multiple motionimage 2220 can receive medical data relating to a clinical condition. Insome examples, the motion image module 220 can also generate a firstmotion image responsive to the medical data, the first motion imagedisplaying a clinical condition in a display configured to appear to auser as similar to a storm on a color weather radar map. In someembodiments, animation of the clinical condition over time is generatedas a series of images of increasing time to display a moving picture ofthe clinical condition, wherein the map is divided into sections thatrepresent clinically differentiated regions. The multiple motion imagemodule 2220 can also generate a second motion image which displays thesame clinical condition shown in the first motion image as a secondimage along a time axis, the second motion image growing along the timeaxis over time, so that the position of a static image along the firstmotion image at a single point or segment in time can be identified onthe second motion image along the time axis so that the relationship andposition of the static image in the first motion image to the secondmotion image is readily viewed.

It is to be understood that the block diagram of FIG. 22 is not intendedto indicate that the computing device 2200 is to include all of thecomponents shown in FIG. 22. Rather, the computing device 2200 caninclude fewer or additional components not illustrated in FIG. 22 (e.g.,additional memory components, embedded controllers, additional modules,additional network interfaces, etc.). Furthermore, any of thefunctionalities of the multiple motion module 2220 may be partially, orentirely, implemented in hardware and/or in the processor 2202. Forexample, the functionality may be implemented with an applicationspecific integrated circuit, logic implemented in an embeddedcontroller, or in logic implemented in the processor 2202, among others.

FIG. 23 is a process flow diagram of an example method for generatingmultiple motion images. The method 2300 can be implemented with acomputing device, such as the computing device 2200 of FIG. 22.

At block 2302, the multiple motion image module 2220 can receive medicaldata relating to a clinical condition. At block 2304, the multiplemotion image module 2220 can generate a first motion image responsive tothe medical data, the first motion image displaying the clinicalcondition in a display configured to appear to a user as similar to astorm on a color weather radar map and wherein animation of the clinicalcondition over time is generated by the processor as a series of imagesof increasing time to display a moving picture of the clinicalcondition, wherein the map is divided into sections that representclinically differentiated regions. At block 2306, the multiple motionimage module 2220 can generate a second motion image which displays thesame clinical condition shown in the first motion image as a secondimage along a time axis, the second motion image growing along the timeaxis over time, so that the position of a static image along the firstmotion image at a single point or segment in time can be identified onthe second motion image along the time axis so that the relationship andposition of the static image in the first motion image to the secondmotion image is readily viewed.

The process flow diagram of FIG. 23 is not intended to indicate that theoperations of the method 2300 are to be executed in any particularorder, or that all of the operations of the method 2300 are to beincluded in every case. Additionally, the method 2300 can include anysuitable number of additional operations.

One of ordinary skill in the art will appreciate the technical effectdescribed herein which provides improved and alternative motion imagevisualizations of a medical condition. Some embodiments described hereinhave the effect of generating multiple motion images. Conditionallanguage used herein, such as, among others, “can,” “may,” “might,”“could,” “e.g.,” and the like, unless specifically stated otherwise, orotherwise understood within the context as used, is generally intendedto convey that certain embodiments include, while other embodiments donot include, certain features, elements and/or steps. Thus, suchconditional language is not generally intended to imply that features,elements and/or steps are in any way required for one or moreembodiments or that one or more embodiments necessarily include logicfor deciding, with or without author input or prompting, whether thesefeatures, elements and/or steps are included or are to be performed inany particular embodiment.

While the above detailed description has shown, described, and pointedout novel features as applied to various embodiments, it will beunderstood that various omissions, substitutions, and changes in theform and details of the device or process illustrated can be madewithout departing from the spirit of the disclosure. As will berecognized, certain embodiments of the inventions described herein canbe embodied within a form that does not provide all of the features andbenefits set forth herein, as some features can be used or practicedseparately from others. The scope of the inventions is indicated by theappended claims rather than by the foregoing description. All changeswhich come within the meaning and range of equivalency of the claims areto be embraced within their scope.

Example Embodiments

In some embodiments, a patient monitoring system comprises at least oneprocessor programmed to receive medical data relating to a clinicalcondition. The processor can also be programmed to generate a firstmotion image responsive to the medical data, the first motion imagedisplaying the clinical condition in a display configured to appear to auser as similar to a storm on a color weather radar map and whereinanimation of the clinical condition over time is generated by theprocessor as a series of images of increasing time to display a movingpicture of the clinical condition, wherein the map is divided intosections that represent clinically differentiated regions. The processorcan also be programmed to generate a second motion image which displaysthe same clinical condition shown in the first motion image as a secondimage along a time axis, the second motion image growing along the timeaxis over time, so that the position of a static image along the firstmotion image at a single point or segment in time can be identified onthe second motion image along the time axis so that the relationship andposition of the static image in the first motion image to the secondmotion image is readily viewed. In some examples, the processor is alsoprogrammed to provide a time-lapsed image of the clinical condition, thefirst motion image and the second motion image being time linked so thatthe first motion image and the second motion image evolve over timesimultaneously.

In some examples, treatment events are positioned along the time axis ofthe second motion image. Additionally, a trellis display of at least twopatients can be displayed. In some examples, the trellis display issorted by characteristics of the storm. Furthermore, in someembodiments, a histogram is generated adjacent the first motion imageand static images of the condition are viewable by selecting points intime on the histogram.

In some examples, the second motion image is shown with relationship topatient treatment events. In some embodiments, specific simultaneoustimes of the first and second motion images are viewable by selectingsaid times. In some examples, the clinical condition is sepsis.

In some embodiments, a patient monitoring system comprising at least oneprocessor can be programmed to generate an image which displays aclinical condition in a display configured to appear to a user assimilar to a storm on a color weather radar display map. In someexamples, a time-lapsable animation of a patient state over time isgenerated by the processor as a series of images of increasing time todisplay a moving picture of the clinical condition wherein the map isdivided into sections that represent clinically differentiated regionsand wherein at least one possible future state of the clinical conditionis determined and presented on the display as a potential storm path. Insome embodiments, the clinical condition can be sepsis.

In some examples, the potential storm path is shown on the map alongwith a determined level of probability. Additionally, the image caninclude a two dimensional user-facing map, wherein time extends along anaxis away from the user facing map so that each user-facing image on thetwo dimensional user-facing map comprises a segment of time along theimage of the condition. In some embodiments, the map may be scrolledforward or backward over time to view different two dimensional imagesof the condition at different segments of time of the condition. In someexamples, the clinical condition is sepsis.

Additionally, in some embodiments, a second image is generatedcomprising a second two dimensional user-facing map, wherein timeextends along one axis of the two dimensional map so that an image onthe second two dimensional user-facing map can extend over the entireduration of the clinical condition.

In some embodiments, the image is a three dimensional user-facing map,wherein time extends along an axis away from the user facing map so thateach user-facing image on the two dimensional user-facing map comprisesa segment of time along the image of the condition. In some examples,the map may be scrolled forward or backward over time with the threedimensional image of the condition moving toward the two dimensionaluser-facing map when the image is scrolled forward over time.

APPENDIX TO THE SPECIFICATION

define stream Albumin as “Albumin”

-   -   profile severity        -   when low            -   value 3.7, 3.6, 3.5, 3.4, 3.2, 3.0, 2.8, 2.6, 2.4, 2.2,                2.1, 2.0, 1.9, 1.8, 1.7        -   when fall            -   min 3.7, 3.6, 3.5, 3.4, 3.2, 3.0, 2.8, 2.6, 2.4, 2.2,                2.1, 2.0, 1.9, 1.8, 1.7            -   magnitude 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0, 1.2, 1.4,                1.6, 1.8, 2, 2.2, 2.4, 2.6    -   qualify        -   fall on magnitude    -   locate in metabolic;        define stream AnionGap as “Anion Gap”    -   profile severity        -   when high            -   value 12, 12.5, 13, 13.5, 14, 14.5, 15, 15.5, 16, 17,                18, 19, 20, 21, 22        -   when rise            -   max 12, 12.5, 13, 13.5, 14, 14.5, 15, 15.5, 16, 17, 18,                19, 20, 21, 22            -   magnitude 1, 2, 3, 3.5, 4, 4.5, 5, 5.5, 6, 6.5, 7, 7.5,                8, 8.5, 9    -   qualify        -   rise on magnitude    -   locate in acidbase;        define stream Bands as “Bands”    -   profile severity        -   when high            -   value start with 4 increase by 1        -   when rise            -   max start with 4 increase by 1        -   magnitude start with 3 increase by 1    -   qualify        -   rise on magnitude    -   locate in inflammatory;        define stream BandsAbs as “Bands Abs”    -   profile severity        -   when high            -   value 1.2, 1.4, 1.6, 1.7, 1.8, 1.9, 2.0, 2.2, 2.4, 2.6,                2.8, 3.0, 3.2, 3.6, 4.0        -   when rise            -   max 1.2, 1.4, 1.6, 1.7, 1.8, 1.9, 2.0, 2.2, 2.4, 2.6,                2.8, 3.0, 3.2, 3.6, 4.0            -   magnitude 0.1, 0.15, 0.18, 0.2, 0.25, 0.3, 0.35, 0.4,                0.5, 0.6, 0.8, 1.0, 1.5, 2.0, 2.5    -   qualify        -   rise on magnitude    -   locate in inflammatory;        define stream BaseDeficit as “Arterial Base Deficit”    -   profile severity        -   when high            -   value start with 1 increase by 0.3        -   when rise            -   max start with 0.3 increase by 0.3            -   slopeindays start with 0.3 increase by 0.2            -   magnitude start with 0.3 increase by 0.2            -   percentchange start with 10 increase by 5        -   when fall            -   slopeindays start with −0.3 decrease by 0.2    -   qualify        -   rise on magnitude    -   locate in acidbase;        define stream Bicarb as “Bicarbonate”, “HCO3, Arterial”, “TCO2,        Arterial”, “Carbon Dioxide”    -   profile severity        -   when low            -   value 24, 23.5, 23.2, 23, 22, 21, 20, 19, 18, 17, 16,                15, 14, 13, 12        -   when fall            -   min 24, 23.5, 23.2, 23, 22, 21, 20, 19, 18, 17, 16, 15,                14, 13, 12            -   magnitude start with 1.5 increase by 0.5    -   qualify        -   fall on magnitude    -   locate in acidbase;        define stream BPSystolic as “BP Systolic”, “ABPSys”    -   profile severity        -   when low            -   value start with 100 decrease by 5        -   when fall            -   min start with 100 decrease by 5            -   magnitude start with 20 increase by 2    -   qualify        -   fall on magnitude    -   locate in cardiac;        define stream BPMean as “BP Mean”, “ABPMean”    -   profile severity        -   when low            -   value start with 70 decrease by 2        -   when fall            -   min start with 70 decrease by 2            -   magnitude start with 10 increase by 2    -   qualify        -   fall on magnitude    -   locate in cardiac;        define stream BUN as “BUN”    -   profile severity        -   when high            -   value 23, 24, 25, 26, 27, 28, 30, 32, 34, 36, 38, 40,                42, 44, 46        -   when rise            -   slopeindays 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,                14, 15            -   magnitude 2, 4, 6, 8, 10, 12, 14, 16, 18, 20, 22, 24,                26, 28, 30            -   percentchange 2, 3, 4, 6, 8, 16, 20, 24, 28, 32, 36, 40,                44, 48, 52        -   when low            -   value 1|10, 2|9, 3|8, 4|7, 5|6, 6|5, 7|4, 8|3, 9|2,                1|11, 1|10        -   when fall            -   slopeindays −1, −2, −3, −4, −5, −6, −7, −8, −9, −10,                −11, −12, −13, −14, −            -   magnitude 2, 4, 6, 8, 10, 12, 14, 16, 18, 20, 22, 24,                26, 28, 30            -   percentchange 5, 8, 10, 14, 18, 22, 26, 30, 34, 38, 42,                46, 50, 54,    -   qualify        -   rise on magnitude        -   fall on magnitude    -   locate in renal;        define stream Calcium as “Calcium”    -   profile severity        -   when low            -   value 8.6, 8.4, 8.2, 8, 7.8, 7.6, 7.4, 7.2, 7, 6.8, 6.4,                6, 5.5, 5, 4.5        -   when fall            -   min 8.6, 8.4, 8.2, 8, 7.8, 7.6, 7.4, 7.2, 7, 6.8, 6.4,                6, 5.5, 5, 4.5            -   magnitude 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0, 1.2, 1.4,                1.6, 1.8, 2.0, 2.2, 2.4, 2.6    -   qualify        -   fall on magnitude    -   locate in electrolytic;        define stream Chloride as “Chloride”    -   profile severity        -   when high            -   value 106, 107, 108, 109, 110, 111, 112, 113, 114, 115,                116, 117, 118, 119, 120        -   when rise            -   slopeindays 1, 1.5, 2, 3, 3.5, 4, 5, 5.5, 6, 6.5, 7,                7.5, 8, 8.5, 9            -   magnitude 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14,                15            -   percentchange 10, 11, 12, 13, 14, 15, 16, 17, 18, 19,                20, 21, 22, 23, 24        -   when low            -   value 100, 99, 98, 97, 96, 95, 94, 93, 92, 91, 90, 89,                88, 87, 86        -   when fall            -   slopeindays −1, −1.5, −2, −3, −3.5, −4, −5, −5.5, −6,                −6.5, −7, −7.5, −8, −8.5, −9            -   magnitude 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14,                15            -   percentchange 10, 11, 12, 13, 14, 15, 16, 17, 18, 19,                20, 21, 22, 23, 24    -   qualify        -   rise on magnitude        -   fall on magnitude    -   locate in electrolytic;        define stream Creatinine as “Creatinine”    -   profile severity        -   when high            -   value 1, 1.05, 1.1, 1.15, 1.2, 1.25, 1.3, 1.35, 1.4,                1.45, 1.5, 1.55, 1.6, 1.7, 1.8        -   when rise            -   slopeindays 0.01, 0.02, 0.03, 0.06, 0.08, 0.1, 0.12,                0.14, 0.16, 0.2, 0.25, 0.3, 0.4, 0.5, 0.6            -   magnitude 0.02, 0.04, 0.06, 0.1, 0.15, 0.2, 0.3, 0.35,                0.4, 0.45, 0.5, 0.55, 0.6, 0.7, 0.8            -   percentchange 2, 3, 4, 5, 6, 8, 10, 12, 14, 16, 20, 24,                28, 32, 36        -   when low            -   value 0.6, 0.5, 0.4, 0.38, 0.36, 0.34, 0.32, 0.31, 0.3,                0.28, 0.26, 0.24, 0.22, 0.20, 0.18        -   when fall            -   slopeindays −0.01, −0.02, −0.03, −0.06, −0.08, −0.1,                −0.12, −0.14, −0.16, −0.2, −0.25, −0.3, −0.4, −0.5, −0.6            -   magnitude 0.02, 0.04, 0.06, 0.1, 0.15, 0.2, 0.3, 0.35,                0.4, 0.45, 0.5, 0.55, 0.6, 0.7, 0.8            -   percentchange 2, 3, 4, 5, 6, 8, 10, 12, 14, 16, 20, 24,                28, 32, 36    -   qualify        -   rise on magnitude and percentchange        -   fall on magnitude and percentchange    -   locate in renal;        define stream eGFR as “eGFR”    -   profile severity        -   when low            -   value 7159, 8156, 9152, 10148, 11144, 12140, 13134,                14130, 15126        -   when fall            -   slopeindays −1, −2, −3, −4, −5, −6, −7, −8, −9, −10,                −11, −12, −13, −14, −15            -   magnitude 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14,                15            -   percentchange 2, 4, 6, 8, 10, 12, 14, 16, 18, 20, 22,                24, 26, 28, 30    -   qualify        -   fall on magnitude    -   locate in renal;        define stream Fibrinogen as “Fibrinogen”    -   profile severity        -   when low            -   value start with 200 decrease by 7        -   when fall            -   min start with 40 decrease by 3            -   slopeindays start with −20 decrease by 3            -   magnitude start with 40 increase by 3            -   percentchange start with 7 increase by 1        -   when rise            -   slopeindays start with 20 increase by 3    -   qualify        -   fall on magnitude    -   locate in haemostatic;        define stream FIO2 as “FIO2”    -   profile severity        -   when high            -   value start with 24 increase by 6        -   when rise            -   slopeindays start with 4 increase by 2            -   magnitude start with 4 increase by 2            -   percentchange start with 20 increase by 5        -   when fall            -   slopeindays start with −4 decrease by 2    -   qualify        -   rise on magnitude    -   locate in respiratory;        define stream GlucoseAny as “Glucose”, “Fingerstick Glucose”    -   profile severity        -   when high            -   value start with 200 increase by 20        -   when rise            -   max start with 50 increase by 10            -   slopeindays start with 40 increase by 10            -   magnitude start with 50 increase by 10            -   percentchange start with 205 increase by 2        -   when low            -   value start with 55 decrease by 2        -   when fall            -   slopeindays start with −40 decrease by 10    -   qualify        -   rise on magnitude    -   locate in metabolic;        define stream Hematocrit as “Hematocrit”    -   profile severity        -   when high            -   value 43, 44, 45, 45.4, 45.8, 46.2, 46.6, 47, 47.4,                47.8, 48.2, 48.6, 49, 49.5, 50        -   when rise            -   slopeindays 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9,                1.0, 1.2, 1.4, 1.6, 1.8, 2.0            -   magnitude 0.2, 0.4, 0.6, 0.8, 1.0, 1.2, 1.4, 1.6, 1.8,                2.0, 2.4, 2.8, 3.2, 3.6, 4.0            -   percentchange 0.5, 0.75, 1.0, 1.6, 2.0, 2.4, 2.8, 3.2,                3.6, 4.0, 4.8, 5.6, 6.4, 7.2, 8.0        -   when low            -   value 38, 37, 36, 35.5, 35, 34.5, 34, 33.5, 33, 32.5,                32, 31.5, 31, 30.5, 30        -   when fall            -   slopeindays −0.1, −0.2, −0.3, −0.4, −0.5, −0.6, −0.7,                −0.8, −0.9, −1.0, −1.2, −1.4, −1.6, −1.8, −2.0            -   magnitude 0.2, 0.4, 0.6, 0.8, 1.0, 1.2, 1.4, 1.6, 1.8,                2.0, 2.4, 2.8, 3.2, 3.6, 4.0            -   percentchange 0.5, 0.75, 1.0, 1.6, 2.0, 2.4, 2.8, 3.2,                3.6, 4.0, 4.8, 5.6, 6.4, 7.2, 8.0    -   qualify        -   rise on magnitude        -   fall on magnitude    -   locate in Hematologic;        define stream HemoglobinAny as “Hemoglobin”, “Arterial        Hemoglobin”, “Hgb”    -   profile severity        -   when low            -   value start with 11 decrease by 0.5        -   when fall            -   min start with 0.5 decrease by 0.02            -   slopeindays start with −0.5 decrease by 0.05            -   magnitude start with 0.5 increase by 0.2            -   percentchange start with 8 increase by 1        -   when rise            -   slopeindays start with 0.5 increase by 0.05    -   qualify        -   fall on magnitude    -   locate in hematologic;        define stream IonCalcium as “Ionized Calcium”    -   profile severity        -   when low            -   value 4.7, 4.6, 4.5, 4.4, 4.3, 4.2, 4.1, 4.0, 3.9, 3.8,                3.6, 3.4, 3.2, 3.0, 2.8        -   when fall            -   min 4.7, 4.6, 4.5, 4.4, 4.3, 4.2, 4.1, 4.0, 3.9, 3.8,                3.6, 3.4, 3.2, 3.0, 2.8            -   magnitude start with 0.4 increase by 0.2    -   qualify        -   fall on magnitude    -   locate in electrolytic;        define stream Lactate as “Lactate”    -   profile severity        -   when high            -   value 1.8, 2.0, 2.2, 2.4, 2.6, 2.8, 3, 3.5, 4, 5, 6, 7,                8, 9, 10        -   when rise            -   max 1.8, 2.0, 2.2, 2.4, 2.6, 2.8, 3, 3.5, 4, 5, 6, 7, 8,                9, 10            -   magnitude 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 1.0, 1.5, 2.0,                2.5, 3.0, 3.5, 4.0, 4.5, 5.0    -   qualify        -   rise on magnitude    -   locate in acidbase;        define stream LDH as “LDH”    -   profile severity        -   when high            -   value 140, 150, 160, 170, 180, 200, 220, 240, 260, 280,                300, 320, 340, 360, 380        -   when rise            -   slopeindays 5, 6, 7, 8, 9, 10, 20, 30, 40, 50, 60, 70,                80, 90, 100            -   percentchange 7, 8, 9, 10, 20, 30, 40, 50, 60, 70, 80,                90, 100, 150, 200        -   when low            -   value 80, 75, 70, 65, 60, 55, 50, 45, 40, 35, 30, 25,                20, 10, 0        -   when fall            -   slopeindays −4, −5, −6, −7, −8, −9, −10, −15, −20, −25,                −30, −35, −40, −45, −50            -   percentchange 5, 6, 7, 8, 9, 10, 15, 20, 30, 40, 50, 60,                70, 80, 90    -   qualify        -   rise on percentchange        -   fall on percentchange    -   locate in misc;        define stream Lymphocytes as “Lymphocytes”    -   profile severity        -   when high            -   value 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51,                52, 53, 54        -   when rise            -   slopeindays 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14,                15, 16            -   magnitude 4, 6, 8, 10, 12, 14, 16, 18, 20, 22, 24, 26,                28, 30, 32            -   percentchange 4, 6, 8, 10, 12, 14, 16, 18, 20, 22, 24,                26, 28, 30, 32    -   qualify        -   rise on magnitude    -   locate in inflammatory;        define stream LymphocytesAbs as “Lymphocytes Abs”    -   profile severity        -   when high            -   value 3.8, 3.9, 4.0, 4.2, 4.4, 4.8, 5.5, 6, 6.5, 7, 7.5,                8, 9, 10, 11        -   when rise            -   slopeindays 0.025, 0.05, 0.1, 0.15, 0.2, 0.25, 0.3, 0.4,                0.6, 0.8, 1.0, 1.2, 1.4, 1.6, 1.8            -   percentchange 7, 8, 9, 10, 20, 30, 40, 50, 60, 70, 80,                90, 100, 150, 200        -   when low            -   value 1.1, 1.0, 0.9, 0.8, 0.75, 0.7, 0.65, 0.6, 0.55,                0.5, 0.45, 0.4, 0.3, 0.2, 0.1        -   when fall            -   slopeindays −0.025, −0.05, −0.1, −0.15, −0.2, −0.25,                −0.3, −0.4, −0.6, −0.8, −1.0, −1.2, −1.4, −1.6, −1.8            -   percentchange 2, 4, 6, 8, 10, 15, 20, 25, 30, 40, 50,                60, 70, 80, 90    -   qualify        -   rise on percentchange        -   fall on percentchange    -   locate in inflammatory;        define stream MetamyelocyteNeut as “Metamyelocytes”    -   profile severity        -   when high            -   value 1410.00001, 1510.001    -   locate in inflammatory;        define stream MinuteVolume as “Minute Volume”    -   profile severity        -   when high            -   value start with 12 increase by 0.6        -   when rise            -   slopeindays start with 2 increase by 0.5            -   magnitude start with 2 increase by 0.5            -   percentchange start with 20 increase by 5        -   when fall            -   slopeindays start with −2 decrease by 0.5    -   qualify        -   rise on magnitude    -   locate in respiratory;        define stream Monocytes as “Monocytes”    -   profile severity        -   when high            -   value 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21,                22, 23, 24        -   when rise            -   max 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15            -   slopeinhours 0.2, 0.4, 0.6, 1.0, 1.4, 1.8, 2.2, 2.6,                3.0, 3.4, 3.8, 4.2, 4.6, 5.0, 5.4            -   percentchange 4, 5, 6, 7, 8, 9, 10, 20, 30, 40, 50, 60,                70, 80, 100        -   when low            -   value 1|4, 4|3, 7|2, 10|1, 13|0        -   when fall            -   /* min 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15                */            -   slopeinhours −0.2, −0.4, −0.6, −1.0, −1.4, −1.8, −2.2,                −2.6, −3.0, −3.4, −3.8, −4.2, −4.6, −5.0, −5.4            -   percentchange 4, 5, 6, 7, 8, 9, 10, 20, 30, 40, 50, 60,                70, 80, 100    -   qualify        -   rise on percentchange        -   fall on percentchange    -   locate in inflammatory;        define stream Neutrophils as “Neutrophils”    -   profile severity        -   when high            -   value 70, 72, 74, 76, 78, 80, 82, 84, 86, 88, 90, 92,                94, 96, 98        -   when rise            -   slopeindays 4, 6, 8, 10, 12, 14, 16, 18, 20, 22, 24, 26,                28, 30, 32            -   magnitude 4, 6, 8, 10, 12, 14, 16, 18, 20, 24, 28, 32,                36, 40, 44            -   percentchange 4, 6, 8, 10, 14, 18, 24, 28, 32, 36, 40,                44, 48, 52, 56        -   when low            -   value 51, 50, 49, 48, 47, 46, 44, 42, 40, 38, 34, 30,                26, 22, 18        -   when fall            -   slopeindays −4, −6, −8, −10, −12, −14, −16, −18, −20,                −22, −24, −26, −28, −30, −32            -   magnitude 4, 6, 8, 10, 12, 14, 16, 18, 20, 24, 28, 32,                36, 40, 44            -   percentchange 4, 6, 8, 10, 14, 18, 24, 28, 32, 36, 40,                44, 48, 52, 56    -   qualify        -   rise on magnitude        -   fall on magnitude    -   locate in inflammatory;        define stream NeutrophilsAbs as “Neutrophils Abs”    -   profile severity        -   when high            -   value 8.5, 9, 9.5, 10, 10.5, 11, 12, 13, 14, 15, 16, 17,                18, 19, 21        -   when rise            -   max 8.5, 9, 9.5, 10, 10.5, 11, 12, 13, 14, 15, 16, 17,                18, 19, 21            -   magnitude start with 1 increase by 1        -   when low            -   value start with 2 decrease by 0.1        -   when fall            -   min start with 3 decrease by 0.2    -   qualify        -   rise on magnitude    -   locate in inflammatory;        define stream NucleatedRBC as “Nucleated RBC”    -   profile severity        -   when high            -   value 14|0.00001, 15|0.001    -   locate in inflammatory;        define stream NucleatedRBCabs as “Nucleated RBC Abs”    -   profile severity        -   when high            -   value 14|0.00001, 15|0.001    -   locate in inflammatory;        define stream OxSat as “SpO2”, “02 SAT, Arterial”, “SaO2”    -   profile severity        -   when low            -   value start with 93 decrease by 1        -   when fall            -   min start with 2 decrease by 0.05            -   slopeindays start with −4 decrease by 2            -   magnitude start with 4 increase by 2            -   percentchange start with 4 increase by 1        -   when rise            -   slopeindays start with 4 increase by 2    -   qualify        -   fall on magnitude    -   locate in respiratory;        define stream PHBlood as “pH, Arterial”, “PH”    -   profile severity        -   when low            -   value start with 7.33 decrease by 0.02        -   when fall            -   magnitude start with 0.0020 increase by 0.0015    -   qualify        -   fall on magnitude    -   locate in acidbase;        define stream PaCO2 as “Arterial PaCO2”    -   profile severity        -   when low            -   value start with 34 decrease by 1        -   when fall            -   min start with 4 decrease by 0.5            -   slopeindays start with −4 decrease by 0.5            -   magnitude start with 4 increase by 0.5            -   percentchange start with 12 increase by 2        -   when rise            -   slopeindays start with 4 increase by 0.5    -   qualify        -   fall on magnitude    -   locate in respiratory;        define stream Platelets as “Platelets”    -   profile severity        -   when low            -   value 160, 150, 140, 130, 120, 110, 100, 90, 80, 70, 60,                50, 40, 30,        -   when fall            -   min 160, 150, 140, 130, 120, 110, 100, 90, 80, 70, 60,                50, 40, 30,            -   magnitude start with 40 increase by 12    -   qualify        -   fall on magnitude    -   locate in haemostatic;        define stream Potassium as “Potassium”    -   profile severity        -   when high            -   value 4.8, 4.9, 5.0, 5.1, 5.2, 5.3, 5.4, 5.5, 5.6, 5.7,                5.8, 5.9, 6.0, 6.1, 6.2        -   when rise            -   slopeindays 0.02, 0.04, 0.06, 0.08, 0.10, 0.12, 0.14,                0.18, 0.22, 0.26, 0.30, 0.34, 0.38, 0.42, 0.46            -   magnitude 0.04, 0.08, 0.12, 0.16, 0.20, 0.24, 0.26,                0.30, 0.34, 0.38, 0.42, 0.46, 0.50, 0.54, 0.58            -   percentchange 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,                14, 15        -   when low            -   value 3.7, 3.6, 3.5, 3.4, 3.3, 3.2, 3.1, 3.0, 2.9, 2.8,                2.7, 2.6, 2.5, 2.4, 2.3        -   when fall            -   slopeindays −0.02, −0.04, −0.06, −0.08, −0.10, −0.12,                −0.14, −0.18, −0.22, −0.26, −0.30, −0.34, −0.38, −0.42,                −0.46            -   magnitude 0.04, 0.08, 0.12, 0.16, 0.20, 0.24, 0.26,                0.30, 0.34, 0.38, 0.42, 0.46, 0.50, 0.54, 0.58            -   percentchange 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,                14, 15    -   qualify        -   rise on magnitude        -   fall on magnitude    -   locate in electrolytic;        define stream HR as “Pulse”, “Heart Rate”    -   profile severity        -   when high    -   value start with 90 increase by 5        -   when rise            -   slopeindays start with 15 increase by 2            -   magnitude start with 15 increase by 2            -   percentchange start with 20 increase by 5        -   when fall            -   min start with 90 decrease by 5            -   magnitude start with 15 increase by 5    -   qualify        -   rise on magnitude        -   fall on magnitude    -   locate in cardiac;        define stream Procalcitonin as “Procalcitonin”    -   profile severity        -   when high            -   value start with 0.15 increase by 0.05        -   when rise            -   slopeindays start with 0.2 increase by 0.03            -   magnitude start with 0.2 increase by 0.05            -   percentchange start with 10 increase by 2        -   when fall            -   slopeindays start with −0.2 decrease by 0.03    -   qualify        -   rise on magnitude    -   locate in inflammatory;        define stream RespiratoryRate as “Respiratory Rate”    -   profile severity        -   when high            -   value start with 18 increase by 1        -   when rise            -   max start with 18 increase by 1            -   magnitude start with 4 increase by 1    -   qualify        -   rise on magnitude    -   locate in respiratory;        define stream SegsAbs as “Segs Abs”    -   profile severity        -   when high            -   value 6.5, 6.75, 7, 7.2, 7.4, 7.6, 8, 9, 10, 11, 13, 15,                17, 19, 21        -   when rise            -   slopeindays 0.25, 0.5, 0.75, 1, 2, 3, 4, 5, 6, 8, 10,                12, 14, 16, 18            -   percentchange 4, 6, 8, 10, 20, 30, 40, 50, 60, 70, 80,                90, 100, 120, 140        -   when low            -   value 2, 1.9, 1.7, 1.6, 1.5, 1.4, 1.3, 1.2, 1.1, 1, 0.8,                0.6, 0.5, 0.4, 0.3        -   when fall            -   slopeindays −0.1, −0.15, −0.2, −0.3, −0.4, −0.5, −0.75,                −1.0, −1.5, −2, −2.5, −3, −3.5, −4, −4.5            -   percentchange 4, 5, 6, 8, 10, 12, 15, 20, 30, 40, 50,                60, 70, 80, 90    -   qualify        -   rise on percentchange        -   fall on percentchange    -   locate in inflammatory;        define stream Segs as “Segs”    -   profile severity        -   when high            -   value 61, 62, 63, 64, 66, 68, 70, 74, 78, 84, 88, 92,                94, 96, 98        -   when rise            -   slopeindays 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,                14, 15            -   magnitude 2, 3, 4, 6, 8, 10, 12, 14, 16, 18, 20, 22, 24,                26, 30            -   percentchange 2, 3, 4, 5, 8, 12, 16, 20, 25, 30, 40, 50,                60, 70, 80        -   when low            -   value 34, 33, 32, 31, 30, 28, 26, 24, 22, 20, 18, 14,                10, 8, 6        -   when fall            -   slopeindays −1, −2, −3, −4, −5, −6, −7, −8, −9, −10,                −11, −12, −13, −14, −15            -   magnitude 2, 3, 4, 6, 8, 10, 12, 14, 16, 18, 20, 22, 24,                26, 30            -   percentchange 2, 3, 4, 5, 8, 12, 16, 20, 25, 30, 40, 50,                60, 70, 80    -   qualify        -   rise on magnitude        -   fall on magnitude    -   locate in inflammatory;        define stream Sodium as “Sodium”    -   profile severity        -   when high            -   value 143, 144, 145, 146, 147, 148, 149, 150, 151, 152,                153, 154, 155, 156, 157        -   when rise            -   slopeindays 0.4, 0.6, 0.8, 1, 1.4, 1.8, 2.2, 2.6, 3,                3.4, 3.8, 4.2, 4.6, 5.0, 5.4            -   magnitude 1, 2, 2.4, 2.8, 3.2, 3.6, 4, 4.4, 4.8, 5.2,                5.6, 6, 6.4, 6.8, 7.2            -   percentchange 0.5, 0.8, 1, 1.4, 1.6, 1.8, 2, 2.4, 2.8,                3.2, 3.6, 4.0, 4.4, 4.8, 5.2        -   when low            -   value 137, 136, 135, 134, 133, 132, 131, 130, 129, 128,                127, 126, 125, 124, 123        -   when fall            -   slopeindays −0.4, −0.6, −0.8, −1, −1.4, −1.8, −2.2,                −2.6, −3, −3.4, −3.8, −4.2, −4.6, −5.0, −5.4            -   magnitude 1, 2, 2.4, 2.8, 3.2, 3.6, 4, 4.4, 4.8, 5.2,                5.6, 6, 6.4, 6.8, 7.2            -   percentchange 0.5, 0.8, 1, 1.4, 1.6, 1.8, 2, 2.4, 2.8,                3.2, 3.6, 4.0, 4.4, 4.8, 5.2    -   qualify        -   rise on magnitude        -   fall on magnitude    -   locate in electrolytic;        define stream TemperatureC as “Temperature C”    -   profile severity        -   when high            -   value 37.22, 37.33, 37.44, 37.56, 37.67, 37.78, 38.06,                38.33, 38.61, 38.89, 39.44, 40.00, 40.56, 41.11, 41.67        -   when rise            -   max 37.22, 37.33, 37.44, 37.56, 37.67, 37.78, 38.06,                38.33, 38.61, 38.89, 39.44, 40.00, 40.56, 41.11, 41.67            -   magnitude 0.22, 0.28, 0.33, 0.39, 0.44, 0.50, 0.56,                0.78, 1.00, 1.22, 1.44, 1.67, 1.78, 1.89, 2.00        -   when low            -   value start with 36.33 decrease by 0.056        -   when fall            -   min start with 36.33 decrease by 0.056            -   magnitude 0.22, 0.28, 0.33, 0.39, 0.44, 0.50, 0.56,                0.78, 1.00, 1.22, 1.44, 1.67, 1.78, 1.89, 2.00    -   qualify        -   rise on magnitude        -   fall on magnitude    -   locate in inflammatory;        define stream TemperatureF as “Temperature F”    -   profile severity        -   when high            -   value 99, 99.2, 99.4, 99.6, 99.8, 100, 100.5, 101,                101.5, 102, 103, 104, 105, 106, 107        -   when rise            -   max 99, 99.2, 99.4, 99.6, 99.8, 100, 100.5, 101, 101.5,                102, 103, 104, 105, 106, 107            -   magnitude 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0, 1.4, 1.8,                2.2, 2.6, 3.0, 3.2, 3.4, 3.6        -   when low            -   value start with 97.4 decrease by 0.1        -   when fall            -   min start with 97.4 decrease by 0.1            -   magnitude 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0, 1.4, 1.8,                2.2, 2.6, 3.0, 3.2, 3.4, 3.6    -   qualify        -   rise on magnitude        -   fall on magnitude    -   locate in inflammatory;        define stream WBC as “WBC”    -   profile severity        -   when high            -   value 12.5, 13, 13.5, 14, 15.5, 16, 17, 18, 19, 20, 21,                22, 23, 25, 27        -   when rise            -   max 12.5, 13, 13.5, 14, 15.5, 16, 17, 18, 19, 20, 21,                22, 23, 25, 27            -   magnitude start with 2 increase by 1        -   when low            -   value 4.2, 4.1, 4.0, 3.9, 3.8, 3.7, 3.5, 3.3, 3.1, 2.8,                2.6, 2.4, 2.0, 1.6, 1.2        -   when fall            -   min 4.2, 4.1, 4.0, 3.9, 3.8, 3.7, 3.5, 3.3, 3.1, 2.8,                2.6, 2.4, 2.0, 1.6, 1.2    -   qualify        -   rise on magnitude and max    -   locate in inflammatory;        —Streams without Severity

-   define stream AaDO2 as “AaDO2” locate in respiratory;

-   define stream ABP_Diastolic_NBP as “ABP Diastolic NBP” locate in    hematologic;

-   define stream Alk_Phos as “Alk Phos” locate in metabolic;

-   define stream ALT_SGPT as “ALT(SGPT)” locate in hepatic;

-   define stream Amylase as “Amylase” locate in inflammatory;

-   define stream APTT as “APTT” locate in haemostatic;

-   define stream Arterial_Base_Excess as “Arterial Base Excess” locate    in acidbase;

-   define stream Arterial_Glucose as “Glucose Art” locate in metabolic;

-   define stream Arterial_Hematocrit as “Hematocrit Art” locate in    hematologic;

-   define stream Arterial_PaO2 as “Arterial PaO2” locate in    respiratory;

-   define stream Arterial_Potassium as “Potassium Art” locate in    electrolytic;

-   define stream Arterial_Sodium as “Sodium Art” locate in    electrolytic;

-   define stream AST_SGOT as “AST(SGOT)” locate in inflammatory;

-   define stream Basophils as “Basophils” locate in metabolic;

-   define stream Bilirubin_Direct as “Bilirubin Direct” locate in    hematologic;

-   define stream Bilirubin_Total as “Bilirubin Total” locate in    electrolytic;

-   define stream BIPAP_IPAP as “BIPAP-IPAP” locate in respiratory;

-   define stream BIPAP_EPAP as “BIPAP-EPAP” locate in respiratory;

-   define stream BNP as “BNP” locate in cardiac;

-   define stream CaO2 as “CaO2” locate in respiratory;

-   define stream CK_MB as “CK-MB” locate in inflammatory;

-   define stream CK_Total as “CK Total” locate in renal;

-   define stream CVP as “CVP” locate in cardiac;

-   define stream D_Dimer as “D-Dimer” locate in haemostatic;

-   define stream Eosinophils as “Eosinophils” locate in inflammatory;

-   define stream Eosinophils_Abs as “Eosinophils Abs” locate in    inflammatory;

-   define stream INR as “INR” locate in haemostatic;

-   define stream Lactic_Acid as “Lactic Acid” locate in acidbase;

-   define stream Lipase as “Lipase” locate in inflammatory;

-   define stream Lymph_Atypical_Abs as “Lymph Atypical Abs” locate in    inflammatory;

-   define stream MCH as “MCH” locate in hematologic;

-   define stream MCHC as “MCHC” locate in hematologic;

-   define stream MCV as “MCV” locate in hematologic;

-   define stream MPV as “MPV” locate in hematologic;

-   define stream Magnesium as “Magnesium” locate in electrolytic;

-   define stream Metamyelocytes_Abs as “Metamyelocytes Abs” locate in    inflammatory;

-   define stream Myelocyte_Abs as “Myelocyte Abs” locate in    inflammatory;

-   define stream Monocytes_Abs as “Monocytes Abs” locate in    inflammatory;

-   define stream Myelocyte as “Myelocyte” locate in inflammatory;

-   define stream O2_Flow as “O2 Flow” locate in respiratory;

-   define stream Osmolality as “Osmolality” locate in metabolic;

-   define stream PEEP as “PEEP” locate in respiratory;

-   define stream Phosphorus as “Phosphorus” locate in electrolytic;

-   define stream Pressure_Support as “Pressure Support” locate in    respiratory;

-   define stream PT as “PT” locate in haemostatic;

-   define stream RBC as “RBC” locate in hematologic;

-   define stream RDW_CV as “RDW-CV” locate in hematologic;

-   define stream SaO2_Calculated as “SaO2 Calc” locate in respiratory;

-   define stream Spon_RR_Mech as “Spon RR (Mech.)” locate in    respiratory;

-   define stream Spon_Vt_L_Mech as “Spon. Vt (L) (Mech.)” locate in    respiratory;

-   define stream Total_Protein as “Total Protein” locate in    respiratory;

-   define stream Troponin as “Troponin” locate in respiratory;

-   define stream Uric_Acid as “Uric Acid” locate in metabolic;    —Temp

-   Identify TempRiseOrHighMarginal as TemperatureFRiseMarginal or

-   TemperatureFHighMarginal Locate in inflammatory;

-   Identify TempRiseOrHighMild as TemperatureFRiseMild or    TemperatureFHighMild Locate in inflammatory;

-   Identify TempRiseOrHighModerate as TemperatureFRiseModerate or    TemperatureFHighModerate Locate in inflammatory;

-   Identify TempRiseOrHighSevere as TemperatureFRiseSevere or    TemperatureFHighSevere Locate in inflammatory;

-   Identify TempRiseOrHighProfound as TemperatureFRiseProfound or    TemperatureFHighMild Locate in inflammatory;

-   Identify TempFallOrLowMarginal as TemperatureFFallMarginal or    TemperatureFLowMarginal Locate in inflammatory;

-   Identify TempFallOrLowMild as TemperatureFFallMild or    TemperatureFLowMild Locate in inflammatory;

-   Identify TempFallOrLowMod as TemperatureFFallModerate or    TemperatureFLowModerate Locate in inflammatory;

-   Identify TempFallOrLowSevere as TemperatureFFallSevere or    TemperatureFLowSevere Locate in inflammatory;

-   Identify TempFallOrLowProfound as TemperatureFFallProfound or    TemperatureFLowProfound Locate in inflammatory;

-   Identify TempBiphasicMarginal as TemperatureFRiseMarginal and    TemperatureFFall within 1d Locate in inflammatory;

-   Identify TempBiphasicMild as TemperatureFRiseMild and    TemperatureFFall within 1d Locate in inflammatory;

-   Identify TempBiphasicMod as TemperatureFRiseModerate and    TemperatureFFall within 1d Locate in inflammatory;

-   Identify TempBiphasicSevere as TemperatureFRiseSevere and    TemperatureFFall within 1d Locate in inflammatory;

-   Identify TempBiphasicProfound as TemperatureFRiseProfound and    TemperatureFFall within 1d Locate in inflammatory;    —Band/BandAbs Rise or High

-   identify BandsRiseOrHighMarginal as BandsRiseMarginal or    BandsHighMarginal locate in inflammatory;

-   identify BandsRiseOrHighMild as BandsRiseMild or BandsHighMild    locate in inflammatory;

-   identify BandsRiseOrHighMod as BandsRiseModerate or    BandsHighModerate locate in inflammatory;

-   identify BandsRiseOrHighSevere as BandsRiseSevere or BandsHighSevere    locate in inflammatory;

-   identify BandsRiseOrHighProfound as BandsRiseProfound or    BandsHighProfound locate in inflammatory;

-   identify BandsAbsRiseOrHighMarginal as BandsAbsRiseMarginal or    BandsAbsHighMarginal locate in inflammatory;

-   identify BandsAbsRiseOrHighMild as BandsAbsRiseMild or    BandsAbsHighMild locate in inflammatory;

-   identify BandsAbsRiseOrHighMod as BandsAbsRiseModerate or    BandsAbsHighModerate locate in inflammatory;

-   identify BandsAbsRiseOrHighSevere as BandsAbsRiseSevere or    BandsAbsHighSevere locate in inflammatory;

-   identify BandsAbsRiseOrHighProfound as BandsAbsRiseProfound or    BandsAbsHighProfound locate in inflammatory;    —WBC Rise or Fall

-   identify WBCRiseOrHighMarginal as WBCRiseMarginal or WBCHighMarginal    locate in inflammatory;

-   identify WBCRiseOrHighMild as WBCRiseMild or WBCHighMild locate in    inflammatory;

-   identify WBCRiseOrHighMod as WBCRiseModerate or WBCHighModerate    locate in inflammatory;

-   identify WBCRiseOrHighSevere as WBCRiseSevere or WBCHighSevere    locate in inflammatory;

-   identify WBCRiseOrHighProfound as WBCRiseProfound or WBCHighProfound    locate in inflammatory;

-   identify WBCLowOrFallMarginal as WBCFallMarginal or WBCLowMarginal    locate in inflammatory;

-   identify WBCLowOrFallMild as WBCFallMild or WBCLowMild locate in    inflammatory;

-   identify WBCLowOrFallMod as WBCFallModerate or WBCLowModerate locate    in inflammatory;

-   identify WBCLowOrFallSevere as WBCFallSevere or WBCLowSevere locate    in inflammatory;

-   identify WBCLowOrFallProfound as WBCFallProfound or WBCLowProfound    locate in inflammatory;    —Neutrophils/Neutrophils Rise or High

-   identify NeutrophilsHighOrRiseMarginal as NeutrophilsRiseMarginal or    NeutrophilsHighMarginal locate in inflammatory;

-   identify NeutrophilsHighOrRiseMild as NeutrophilsRiseMild or    NeutrophilsHighMild locate in inflammatory;

-   identify NeutrophilsHighOrRiseMod as NeutrophilsRiseModerate or    NeutrophilsHighModerate locate in inflammatory;

-   identify NeutrophilsHighOrRiseSevere as NeutrophilsRiseSevere or    NeutrophilsHighSevere locate in inflammatory;

-   identify NeutrophilsHighOrRiseProfound as NeutrophilsRiseProfound or    NeutrophilsHighProfound locate in inflammatory;

-   identify NeutrophilsAbsHighOrRiseMarginal as    NeutrophilsAbsRiseMarginal or NeutrophilsAbsHighMarginal locate in    inflammatory; identify NeutrophilsAbsHighOrRiseMild as    NeutrophilsAbsRiseMild or

-   NeutrophilsAbsHighMild locate in inflammatory;

-   identify NeutrophilsAbsHighOrRiseMod as NeutrophilsAbsRiseModerate    or NeutrophilsAbsHighModerate locate in inflammatory;

-   identify NeutrophilsAbsHighOrRiseSevere as NeutrophilsAbsRiseSevere    or NeutrophilsAbsHighSevere locate in inflammatory;

-   identify NeutrophilsAbsHighOrRiseProfound as    NeutrophilsAbsRiseProfound or NeutrophilsAbsHighProfound locate in    inflammatory;    —Neutrophils/Neutrophils Low or Fall

-   identify NeutrophilsLowOrFallMarginal as NeutrophilsFallMarginal or    NeutrophilsLowMarginal locate in inflammatory;

-   identify NeutrophilsLowOrFallMild as NeutrophilsFallMild or    NeutrophilsLowMild locate in inflammatory;

-   identify NeutrophilsLowOrFallMod as NeutrophilsFallModerate or    NeutrophilsLowModerate locate in inflammatory;

-   identify NeutrophilsLowOrFallSevere as NeutrophilsFallSevere or    NeutrophilsLowSevere locate in inflammatory;

-   identify NeutrophilsLowOrFallProfound as NeutrophilsFallProfound or    NeutrophilsLowProfound locate in inflammatory;

-   identify NeutrophilsAbsLowOrFallMarginal as    NeutrophilsAbsFallMarginal or NeutrophilsAbsLowMarginal locate in    inflammatory;

-   identify NeutrophilsAbsLowOrFallMild as NeutrophilsAbsFallMild or    NeutrophilsAbsLowMild locate in inflammatory;

-   identify NeutrophilsAbsLowOrFallMod as NeutrophilsAbsFallModerate or    NeutrophilsAbsLowModerate locate in inflammatory;

-   identify NeutrophilsAbsLowOrFallSevere as NeutrophilsAbsFallSevere    or NeutrophilsAbsLowSevere locate in inflammatory;

-   identify NeutrophilsAbsLowOrFallProfound as    NeutrophilsAbsFallProfound or NeutrophilsAbsLowProfound locate in    inflammatory;    —LymphocytesAbs Low or Fall

-   identify LymphocytesAbsLowOrFallMarginal as    LymphocytesAbsFallMarginal or LymphocytesAbsLowMarginal locate in    inflammatory;

-   identify LymphocytesAbsLowOrFallMild as LymphocytesAbsFallMild or    LymphocytesAbsLowMild locate in inflammatory;

-   identify LymphocytesAbsLowOrFallMod as LymphocytesAbsFallModerate or    LymphocytesAbsLowModerate locate in inflammatory;

-   identify LymphocytesAbsLowOrFallSevere as LymphocytesAbsFallSevere    or LymphocytesAbsLowSevere locate in inflammatory;

-   identify LymphocytesAbsLowOrFallProfound as    LymphocytesAbsFallProfound or LymphocytesAbsLowProfound locate in    inflammatory;    —Pathophysiologically Divergence or Decoherence (PD) of    LymphocytesAbs in Relation to Bands Bands Abs indicative of    Inflammation, Stress, or Lymphocyte depletion

-   Identify PDLymphocytesAbsBandsMarginal as BandsRiseorHighMarginal    and

-   LymphocytesAbsFallMarginal within 1d Locate in inflammatory;

-   Identify PDLymphocytesAbsBandsMild as BandsRiseorHighMild and

-   LymphocytesAbsFallMild within 1d Locate in inflammatory;

-   Identify PDLymphocytesAbsBandsMod as BandsRiseorHighMod and

-   LymphocytesAbsFallModerate within 1d Locate in inflammatory;

-   Identify PDLymphocytesAbsBandsSevere as BandsRiseorHighSevere and

-   LymphocytesAbsFallSevere within 1d Locate in inflammatory;

-   Identify PDLymphocytesAbsBandsProfound as BandsRiseorHighProfound    and

-   LymphocytesAbsFallProfound within 1d Locate in inflammatory;

-   identify PDLymphocytesAbsBandsAbsMarginal as    BandsAbsRiseorHighMarginal and

-   LymphocytesAbsFallMarginal within 1d Locate in inflammatory;

-   Identify PDLymphocytesAbsBandsAbsMild as BandsAbsRiseorHighMild and

-   LymphocytesAbsFallMild within 1d Locate in inflammatory;

-   Identify PDLymphocytesAbsBandsAbsMod as BandsAbsRiseorHighMod and

-   LymphocytesAbsFallModerate within 1d Locate in inflammatory;

-   Identify PDLymphocytesAbsBandsAbsSevere as BandsAbsRiseorHighSevere    and

-   LymphocytesAbsFallSevere within 1d Locate in inflammatory;

-   Identify PDLymphocytesAbsBandsAbsProfound as    BandsAbsRiseorHighProfound and

-   LymphocytesAbsFallProfound within 1d Locate in inflammatory;    —Pathophysiologically Divergence or Decoherence (PD) of    LymphocytesAbs in Relation to Neutrophils/NeutrophilsAbs indicative    of Inflammation, Stress, or Lymphocyte depletion identify    PDLymphocytesAbsNeutrophilsAbsMarginal as    NeutrophilsAbsHighorRiseMarginal and LymphocytesAbsFallMarginal    within 1d Locate in inflammatory;

-   Identify PDLymphocytesAbsNeutrophilsAbsMild as    NeutrophilsAbsHighorRiseMild and LymphocytesAbsFallMild within 1d    Locate in inflammatory;

-   Identify PDLymphocytesAbsNeutrophilsAbsMod as    NeutrophilsAbsHighorRiseMod and LymphocytesAbsFallModerate within 1d    Locate in inflammatory;

-   Identify PDLymphocytesAbsNeutrophilsAbsSevere as    NeutrophilsAbsHighorRiseSevere and LymphocytesAbsFallSevere within    1d Locate in inflammatory;

-   Identify PDLymphocytesAbsNeutrophilsAbsProfound as    NeutrophilsAbsHighorRiseProfound and LymphocytesAbsFallProfound    within 1d Locate in inflammatory;

-   identify PDLymphocytesAbsWBCMarginal as WBCRiseorHighMarginal and    LymphocytesAbsFallMarginal within 1d Locate in inflammatory;

-   Identify PDLymphocytesAbsWBCMild as WBCRiseorHighMild and    LymphocytesAbsFallMild within 1d Locate in inflammatory;

-   Identify PDLymphocyteAbssWBCMod as WBCRiseorHighMod and    LymphocytesAbsFallModerate within 1d Locate in inflammatory;

-   Identify PDLymphocytesAbsWBCSevere as WBCRiseorHighSevere and    LymphocytesAbsFallSevere within 1d Locate in inflammatory;

-   Identify PDLymphocytesAbsWBCProfound as WBCRiseorHighProfound and    LymphocytesAbsFallProfound within 1d Locate in inflammatory;    —Pathophysiologically Divergence or Decoherence of WBC and Bands(PD)    indicative of Neutrophil Failure (in relation to WBC)

-   Identify PDWBCBandsMarginal as BandsRiseorHighMarginal and    WBCLowOrFallMarginal within 1d Locate in inflammatory;

-   Identify PDWBCBandsMild as BandsRiseorHighMild and WBCLowOrFallMild    within 1d Locate in inflammatory;

-   Identify PDWBCBandsMod as BandsRiseorHighMod and WBCLowOrFallMod    within 1d Locate in inflammatory;

-   Identify PDWBCBandsSevere as BandsRiseorHighSevere and    WBCLowOrFallSevere within 1d Locate in inflammatory;

-   Identify PDWBCBandsProfound as BandsRiseorHighProfound and    WBCLowOrFallProfound within 1d Locate in inflammatory;

-   Identify PDWBCBandsMod2 as BandsRiseorHighMod and    WBCRiseOrHighMarginal within 1d Locate in inflammatory;

-   Identify PDWBCBandsSevere2 as BandsRiseorHighSevere and    WBCRiseOrHighMild within 1d Locate in inflammatory;

-   Identify PDWBCBandsProfound2 as BandsRiseorHighProfound and    WBCLowOrFallMod within 1d Locate in inflammatory;    —Pathophysiologically Divergence or Decoherence (PD) of Neutrophils    and Bands indicative of Neutrophil Failure (in relation to mature    Neutrophils)

-   Identify PDNeutrophilsBandsMarginal as BandsRiseorHighMarginal and    NeutrophilsLowOrFallMarginal within 1d Locate in inflammatory;

-   Identify PDNeutrophilsBandsMild as BandsRiseorHighMild and    NeutrophilsLowOrFallMild within 1d Locate in inflammatory;

-   Identify PDNeutrophilsBandsMod as BandsRiseorHighMod and    NeutrophilsLowOrFallMod within 1d Locate in inflammatory;

-   Identify PDNeutrophilsBandsSevere as BandsRiseorHighSevere and    NeutrophilsLowOrFallSevere within 1d Locate in inflammatory;

-   Identify PDNeutrophilsBandsProfound as BandsRiseorHighProfound and    NeutrophilsLowOrFallProfound within 1d Locate in inflammatory;

-   Identify PDNeutrophilsBandsMod2 as BandsRiseorHighMod and    NeutrophilsLowOrFallMarginal within 1d Locate in inflammatory;

-   Identify PDNeutrophilsBandsSevere2 as BandsRiseorHighSevere and    NeutrophilsLowOrFallMild within 1d Locate in inflammatory;

-   Identify PDNeutrophilsBandsProfound2 as BandsRiseorHighProfound and    NeutrophilsLowOrFallMod within 1d Locate in inflammatory;

-   Identify PDNeutrophilsAbsBandsMarginal as BandsAbsRiseorHighMarginal    and NeutrophilsAbsLowOrFallMarginal within 1d Locate in    inflammatory;

-   Identify PDNeutrophilsAbsBandsMild as BandsAbsRiseorHighMild and    NeutrophilsAbsLowOrFallMild within 1d Locate in inflammatory;

-   Identify PDNeutrophilsAbsBandsMod as BandsAbsRiseorHighMod and    NeutrophilsAbsLowOrFallMod within 1d Locate in inflammatory;

-   Identify PDNeutrophilsAbsBandsSevere as BandsAbsRiseorHighSevere and    NeutrophilsAbsLowOrFallSevere within 1d Locate in inflammatory;

-   Identify PDNeutrophilsAbsBandsProfound as BandsAbsRiseorHighProfound    and NeutrophilsAbsLowOrFallProfound within 1d Locate in    inflammatory;

-   Identify PDNeutrophilsAbsBandsMod2 as BandsAbsRiseorHighMod and    NeutrophilsAbsLowOrFallMarginal within 1d Locate in inflammatory;

-   Identify PDNeutrophilsAbsBandsSevere2 as BandsAbsRiseorHighSevere    and NeutrophilsAbsLowOrFallMild within 1d Locate in inflammatory;

-   Identify PDNeutrophilsAbsBandsProfound2 as    BandsAbsRiseorHighProfound and NeutrophilsAbsLowOrFallMod within 1d    Locate in inflammatory;    —Neutrophil Failure (Combined)

-   Identify NeutrophilFailureMarginal as PDNeutrophilsBandsMarginal or    PDNeutrophilsAbsBandsMarginal or PDWBCBandsMarginal or    PDNeutrophilsAbsBandsMod2 or PDNeutrophilsBandsMod2 locate in    inflammatory;

-   Identify NeutrophilFailureMild as PDNeutrophilsBandsMild or    PDNeutrophilsAbsBandsMild or PDWBCBandsMild or    PDNeutrophilsAbsBandsSevere2 or PDNeutrophilsBandsSevere2 locate in    inflammatory;

-   Identify NeutrophilFailureMod as PDNeutrophilsBandsMod or    PDNeutrophilsAbsBandsMod or PDWBCBandsMod or    PDNeutrophilsAbsBandsProfound2 or PDNeutrophilsBandsProfound2 locate    in inflammatory;

-   Identify NeutrophilFailureSevere as PDNeutrophilsBandsSevere or    PDNeutrophilsAbsBandsSevere or PDWBCBandsSevere locate in    inflammatory;

-   Identify NeutrophilFailureProfound as PDNeutrophilsBandsProfound or    PDNeutrophilsAbsBandsProfound or PDWBCBandsProfound locate in    inflammatory;    —Bands OR Neutrophil Rise or High

-   identify NeutrophilOrBandsHighOrRiseMarginal as    BandsAbsRiseOrHighMarginal or NeutrophilsAbsHighOrRiseMarginal    locate in inflammatory;

-   identify NeutrophilOrBandsHighOrRiseMild as BandsAbsRiseOrHighMild    or NeutrophilsAbsHighOrRiseMild locate in inflammatory;

-   identify NeutrophilOrBandsHighOrRiseMod as BandsAbsRiseOrHighMild or    NeutrophilsAbsHighOrRiseMod locate in inflammatory;

-   identify NeutrophilOrBandsHighOrRiseSevere as BandsAbsRiseOrHighMild    or NeutrophilsAbsHighOrRiseSevere locate in inflammatory;

-   identify NeutrophilOrBandsHighOrRiseProfound as    BandsAbsRiseOrHighMild or NeutrophilsAbsHighOrRiseProfound locate in    inflammatory;    —Bands AND Neutrophil Rise or High

-   identify NeutrophilANDBandsHighOrRiseMarginal as    BandsAbsRiseOrHighMarginal and NeutrophilsAbsHighOrRiseMarginal    within 1d locate in inflammatory;

-   identify NeutrophilANDBandsHighOrRiseMild as BandsAbsRiseOrHighMild    and NeutrophilsAbsHighOrRiseMild within 1d locate in inflammatory;

-   identify NeutrophilANDBandsHighOrRiseMod as BandsAbsRiseOrHighMild    and NeutrophilsAbsHighOrRiseMod within 1d locate in inflammatory;

-   identify NeutrophilANDBandsHighOrRiseSevere as    BandsAbsRiseOrHighMild and NeutrophilsAbsHighOrRiseSevere within 1d    locate in inflammatory;

-   identify NeutrophilANDBandsHighOrRiseProfound as    BandsAbsRiseOrHighMild and NeutrophilsAbsHighOrRiseProfound within    1d locate in inflammatory;    —Temp and Neutrophil and Band Rise or High

-   identify NeutrophilAndBandAndTempMarginal as TempRiseOrHighMarginal    and NeutrophilANDBandsHighOrRiseMarginal within 1d locate in    inflammatory;

-   identify NeutrophilAndBandAndTempMild as TempRiseOrHighMild and    NeutrophilANDBandsHighOrRiseMild within 1d locate in inflammatory;

-   identify NeutrophilAndBandAndTempMod as TempRiseOrHighModerate and    NeutrophilANDBandsHighOrRiseMod within 1d locate in inflammatory;

-   identify NeutrophilAndBandAndTempSevere as TempRiseOrHighSevere and    NeutrophilANDBandsHighOrRiseSevere within 1d locate in inflammatory;

-   identify NeutrophilAndBandAndTempProfound as TempRiseOrHighProfound    and NeutrophilANDBandsHighOrRiseProfound within 1d locate in    inflammatory;    —Temp or Neutrophil or Band Rise or High

-   identify NeutrophilOrBandOrTempMarginal as TempRiseOrHighMarginal or    NeutrophilOrBandsHighOrRiseMarginal locate in inflammatory;

-   identify NeutrophilOrBandOrTempMild as TempRiseOrHighMild or    NeutrophilOrBandsHighOrRiseMild locate in inflammatory;

-   identify NeutrophilOrBandOrTempMod as TempRiseOrHighModerate or    NeutrophilOrBandsHighOrRiseMod locate in inflammatory;

-   identify NeutrophilOrBandOrTempSevere as TempRiseOrHighSevere or    NeutrophilOrBandsHighOrRiseSevere locate in inflammatory;

-   identify NeutrophilOrBandOrTempProfound as TempRiseOrHighProfound or    NeutrophilOrBandsHighOrRiseProfound locate in inflammatory;    —Biomarker Procalcitonin Rise or High

-   identify ProcalcitoninRiseOrHighMarginal as    ProcalcitoninRiseMarginal or ProcalcitoninHighMarginal locate in    inflammatory;

-   identify ProcalcitoninRiseOrHighMild as ProcalcitoninRiseMild or    ProcalcitoninHighMild locate in inflammatory;

-   identify ProcalcitoninRiseOrHighMod as ProcalcitoninRiseModerate or    ProcalcitoninHighModerate locate in inflammatory;

-   identify ProcalcitoninRiseOrHighSevere as ProcalcitoninRiseSevere or    ProcalcitoninHighSevere locate in inflammatory;

-   identify ProcalcitoninRiseOrHighProfound as    ProcalcitoninRiseProfound or ProcalcitoninHighProfound locate in    inflammatory;    —Neutrophil or Band or Temp and Procalcitonin

-   identify NeutrophilOrBandOrTempProcalcitonMarginal as    NeutrophilOrBandOrTempMarginal and ProcalcitoninRiseOrHighMarginal    within 2d locate in inflammatory;

-   identify NeutrophilOrBandOrTempProcalcitoninMild as    NeutrophilOrBandOrTempMild and ProcalcitoninRiseOrHighMild within 2d    locate in inflammatory;

-   identify NeutrophilOrBandOrTempProcalcitoninMod as    NeutrophilOrBandOrTempMod and ProcalcitoninRiseOrHighMod within 2d    locate in inflammatory;

-   identify NeutrophilOrBandOrTempProcalcitoninSevere as    NeutrophilOrBandOrTempSevere and ProcalcitoninRiseOrHighSevere    within 2d locate in inflammatory;

-   identify NeutrophilOrBandOrTempProcalcitonProfound as    NeutrophilOrBandOrTempProfound and ProcalcitoninRiseOrHighProfound    within 2d locate in inflammatory;

-   identify NeutrophilAndBandAndTempProcalcitonMarginal as    NeutrophilAndBandAndTempMarginal and ProcalcitoninRiseOrHighMarginal    within 2d locate in inflammatory;

-   identify NeutrophilAndBandAndTempProcalcitoninMild as    NeutrophilAndBandAndTempMild and ProcalcitoninRiseOrHighMild within    2d locate in inflammatory;

-   identify NeutrophilAndBandAndTempProcalcitoninMod as    NeutrophilAndBandAndTempMod and ProcalcitoninRiseOrHighMod within 2d    locate in inflammatory;

-   identify NeutrophilAndBandAndTempProcalcitoninSevere as    NeutrophilAndBandAndTempSevere and ProcalcitoninRiseOrHighSevere    within 2d locate in inflammatory;

-   identify NeutrophilAndBandAndTempProcalcitonProfound as    NeutrophilAndBandAndTempProfound and ProcalcitoninRiseOrHighProfound    within 2d locate in inflammatory;    —Respiratory

-   Identify SaO2LowOrFallMarginal as OxSatLowMarginal or    OxSatFallMarginal Locate in respiratory;

-   Identify SaO2LowOrFallMild as OxSatLowMild or OxSatFallMild Locate    in respiratory; Identify SaO2LowOrFallMod as OxS atLowModerate or    OxSatFallModerate Locate in respiratory;

-   Identify SaO2LowOrFallSevere as OxSatLowSevere or OxSatFallSevere    Locate in respiratory;

-   Identify SaO2LowOrFallProfound as OxS atLowProfound or    OxSatFallProfound Locate in respiratory;

-   Identify RRHighOrRiseMarginal as RespiratoryRateHighMarginal or    RespiratoryRateRiseMarginal Locate in respiratory;

-   Identify RRHighOrRiseMild as RespiratoryRateHighMild or    RespiratoryRateRiseMild Locate in respiratory;

-   Identify RRHighOrRiseMod as RespiratoryRateHighModerate or    RespiratoryRateRiseModerate Locate in respiratory;

-   Identify RRHighOrRiseSevere as RespiratoryRateHighSevere or    RespiratoryRateRiseSevere Locate in respiratory;

-   Identify RRHighOrRiseProfound as RespiratoryRateHighProfound or    RespiratoryRateRiseProfound Locate in respiratory;

-   Identify PDSPO2RRMarginal as RRHighOrRiseMarginal and    SaO2LowOrFallMarginal within 1d Locate in respiratory;

-   Identify PDSPO2RRMild as RRHighOrRiseMild and SaO2LowOrFallMild    within 1d Locate in respiratory;

-   Identify PDSPO2RRMod as RRHighOrRiseMod and SaO2LowOrFallMod within    1d Locate in respiratory;

-   Identify PDSPO2RRSevere as RRHighOrRiseSevere and    SaO2LowOrFallSevere within 1d Locate in respiratory;

-   Identify PDSPO2RRProfound as RRHighOrRiseProfound and    SaO2LowOrFallProfound within 1d Locate in respiratory;    —Acid Base

-   Identify BicarbFallOrLowMarginal as BicarbFallMarginal or    BicarbLowMarginal locate in acidbase;

-   Identify BicarbFallOrLowMild as BicarbFallMild or BicarbLowMild    locate in acidbase;

-   Identify BicarbFallOrLowMod as BicarbFallModerate or    BicarbLowModerate locate in acidbase;

-   Identify BicarbFallOrLowSevere as BicarbFallSevere or    BicarbLowSevere locate in acidbase;

-   Identify BicarbFallOrLowProfound as BicarbFallProfound or    BicarbLowProfound locate in acidbase;

-   identify Acidosis as AnionGapRise or AnionGapHigh or PHBloodLow    locate in acidbase; identify AcidosisMarginal as    AnionGapRiseMarginal or AnionGapHighMarginal or PHBloodLowMarginal    locate in acidbase;

-   identify AcidosisMild as AnionGapRiseMild or AnionGapHighMild or    PHBloodLowMild locate in acidbase;

-   identify AcidosisMod as AnionGapRiseModerate or AnionGapHighModerate    or PHBloodLowModerate locate in acidbase;

-   identify AcidosisSevere as AnionGapRiseSevere or AnionGapHighSevere    or PHBloodLowSevere locate in acidbase;

-   identify AcidosisProfound as AnionGapRiseProfound or    AnionGapHighProfound or PHBloodLowProfound locate in acidbase;

-   Identify LactateRiseOrHighMarginal as LactateRiseMarginal or    LactateHighMarginal locate in acidbase;

-   Identify LactateRiseOrHighMild as LactateRiseMild or LactateHighMild    locate in acidbase;

-   Identify LactateRiseOrHighMod as LactateRiseModerate or    LactateHighModerate locate in acidbase;

-   Identify LactateRiseOrHighSevere as LactateRiseSevere or    LactateHighSevere locate in acidbase;

-   Identify LactateRiseOrHighProfound as LactateRiseProfound or    LactateHighProfound locate in acidbase;

-   identify LacticAcidosisMarginal as AcidosisMarginal and    LactateHighMarginal within 9h locate in acidbase;

-   identify LacticAcidosisMild as AcidosisMild and LactateHighMild    within 9h locate in acidbase;

-   identify LacticAcidosisMod as AcidosisMod and LactateHighModerate    within 9h locate in acidbase;

-   identify LacticAcidosisSevere as AcidosisSevere and    LactateHighSevere within 9h locate in acidbase;

-   identify LacticAcidosisProfound as AcidosisProfound and    LactateHighProfound within 9h locate in acidbase;

-   Identify AcidosisOrBicarbFallorLoworLactateMarginal as    AcidosisMarginal or

-   BicarbFallOrLowMarginal or LactateRiseOrHighMarginal or    LacticAcidosisMarginal locate in acidbase;

-   Identify AcidosisOrBicarbFallorLoworLactateMild as AcidosisMild or    BicarbFallOrLowMild or LactateRiseOrHighMild or LacticAcidosisMild    locate in acidbase;

-   Identify AcidosisOrBicarbFallorLoworLactateMod as AcidosisMod or    BicarbFallOrLowMod or LactateRiseOrHighMod or LacticAcidosisMod    locate in acidbase;

-   Identify AcidosisOrBicarbFallorLoworLactateSevere as AcidosisSevere    or BicarbFallOrLowSevere or LactateRiseOrHighSevere or    LacticAcidosisSevere locate in acidbase;

-   Identify AcidosisOrBicarbFallorLoworLactateProfound as    AcidosisProfound or BicarbFallOrLowProfound or    LactateRiseOrHighProfound or LacticAcidosisProfound locate in    acidbase;    —Fall or Low Calcium or Ionized Calcium

-   Identify FallorLowCalciumMarginal as CalciumFallMarginal or    IonCalciumFallMarginal or CalciumLowMarginal or    IonCalciumLowMarginal;

-   Identify FallorLowCalciumMild as CalciumFallMild or    IonCalciumFallMild or CalciumLowMild or IonCalciumLowMild;

-   Identify FallorLowCalciumMod as CalciumFallModerate or    IonCalciumFallModerate or CalciumLowModerate or    IonCalciumLowMarginal;

-   Identify FallorLowCalciumSevere as CalciumFallSevere or    IonCalciumFallSevere or CalciumLowMarginal or IonCalciumLowMarginal;

-   Identify FallorLowCalciumProfound as CalciumFallProfound or    IonCalciumFallProfound or CalciumLowProfound or    IonCalciumLowProfound;    —Haemostatic

-   identify PlateletLowOrFallMarginal as PlateletsFallMarginal or    PlateletsLowMarginal locate in haemostatic;

-   identify PlateletLowOrFallMild as PlateletsFallMild or    PlateletsLowMild locate in haemostatic;

-   identify PlateletLowOrFallModerate as PlateletsFallModerate or    PlateletsLowModerate locate in haemostatic;

-   identify PlateletLowOrFallSevere as PlateletsFallSevere or    PlateletsLowSevere locate in haemostatic;

-   identify PlateletLowOrFallProfound as PlateletsFallProfound or    PlateletsLowProfound locate in haemostatic;    —Pathophysiologic Divergence or Decoherence of Procalcitonin and Low    Temp

-   identify PDProcalcitoninLowTempMarginal as    ProcalcitoninRiseOrHighMarginal and TemperatureFLow within 1d locate    in acidbase, inflammatory;

-   identify PDProcalcitoninLowTempMild as ProcalcitoninRiseOrHighMild    and TemperatureFLow within 1d locate in acidbase, inflammatory;

-   identify PDProcalcitoninLowTempMod as ProcalcitoninRiseOrHighMod and    TemperatureFLow within 1d locate in acidbase, inflammatory;

-   identify PDProcalcitoninLowTempSevere as    ProcalcitoninRiseOrHighSevere and TemperatureFLow within 1d locate    in acidbase, inflammatory;

-   identify PDProcalcitoninLowTempProfound as    ProcalcitoninRiseOrHighProfound and TemperatureFLow within 1d locate    in acidbase, inflammatory;    —Pathophysiologic Divergence or Decoherence Inflammation,    Temperature

-   Identify PDNeutrophilOrBandsTempMarginal as    NeutrophilOrBandOrTempMarginal and TemperatureFLowMarginal within 1d    Locate in inflammatory;

-   Identify PDNeutrophilOrBandsTempMild as NeutrophilOrBandOrTempMild    and TemperatureFLowMild within 1d Locate in inflammatory;

-   Identify PDNeutrophilOrBandsTempMod as NeutrophilOrBandOrTempMod and    TemperatureFLowModerate within 1d Locate in inflammatory;

-   Identify PDNeutrophilOrBandsTempSevere as    NeutrophilOrBandOrTempSevere and TemperatureFLowSevere within 1d    Locate in inflammatory;

-   Identify PDNeutrophilOrBandsTempProfound as    NeutrophilOrBandOrTempProfound and TemperatureFLowProfound within 1d    Locate in inflammatory;

-   Identify PDNeutrophilAndBandsTempMarginal as    NeutrophilAndBandAndTempMarginal and TemperatureFLowMarginal within    1d Locate in inflammatory;

-   Identify PDNeutrophilAndBandsTempMild as    NeutrophilAndBandAndTempMild and TemperatureFLowMild within 1d    Locate in inflammatory;

-   Identify PDNeutrophilAndBandsTempMod as NeutrophilAndBandAndTempMod    and TemperatureFLowModerate within 1d Locate in inflammatory;

-   Identify PDNeutrophilAndBandsTempSevere as    NeutrophilAndBandAndTempSevere and TemperatureFLowSevere within 1d    Locate in inflammatory;

-   Identify PDNeutrophilAndBandsTempProfound as    NeutrophilAndBandAndTempProfound and

-   TemperatureFLowProfound within 1d Locate in inflammatory;    —Inflammatory Augmentation

-   Identify InflammatoryAugmentationMild as    -   NeutrophilOrBandOrTempMild or        -   NeutrophilAndBandsHighOrRiseMild or    -   PDLymphocytesAbsBandsMild or        -   PDLymphocytesAbsNeutrophilsAbsMild or        -   NeutrophilOrBandOrTempProcalcitoninMild or        -   PDProcalcitoninLowTempMild        -   locate in inflammatory;            Identify InflammatoryAugmentationMod as    -   NeutrophilOrBandOrTempMod or        -   NeutrophilAndBandsHighOrRiseMod or    -   PDLymphocytesAbsBandsMod or        -   PDLymphocytesAbsNeutrophilsAbsMod or        -   NeutrophilOrBandOrTempProcalcitoninMod or        -   PDProcalcitoninLowTempMod or        -   PDNeutrophilOrBandsTempMarginal or        -   PDNeutrophilAndBandsTempMarginal or        -   PDNeutrophilOrBandsTempMild or        -   PDNeutrophilAndBandsTempMild or        -   PDNeutrophilOrBandsTempMod or        -   PDNeutrophilAndBandsTempMod or        -   NeutrophilFailureMarginal or        -   NeutrophilFailureMild or        -   NeutrophilFailureMod        -   locate in inflammatory;            Identify InflammatoryAugmentationMarginal as    -   NeutrophilOrBandOrTempMarginal or        -   NeutrophilAndBandsHighOrRiseMarginal or    -   PDLymphocytesAbsBandsMarginal or        -   PDLymphocytesAbsNeutrophilsAbsMarginal or        -   NeutrophilOrBandOrTempProcalcitonMarginal or        -   PDProcalcitoninLowTempMarginal        -   Locate in inflammatory;            Identify InflammatoryAugmentationSevere as    -   NeutrophilOrBandOrTempSevere or        -   NeutrophilAndBandsHighOrRiseSevere or    -   PDLymphocytesAbsBandsSevere or        -   PDLymphocytesAbsNeutrophilsAbsSevere or        -   NeutrophilOrBandOrTempProcalcitoninSevere or        -   PDProcalcitoninLowTempSevere or        -   PDNeutrophilOrBandsTempSevere or        -   PDNeutrophilAndBandsTempSevere or        -   NeutrophilFailureSevere        -   locate in inflammatory;            Identify InflammatoryAugmentationProfound as    -   NeutrophilOrBandOrTempProfound or        -   NeutrophilAndBandsHighOrRiseProfound or    -   PDLymphocytesAbsBandsProfound or        -   PDLymphocytesAbsNeutrophilsAbsProfound or        -   NeutrophilOrBandOrTempProcalcitonProfound or        -   PDProcalcitoninLowTempMarginal or        -   PDNeutrophilOrBandsTempProfound or        -   PDNeutrophilAndBandsTempProfound or        -   NeutrophilFailureProfound        -   locate in inflammatory;            —Inflammation and Haemostatic

-   identify SeqInflammatoryAugmentationPlateletFallMild as    InflammatoryAugmentationMild preceding PlateletsFallMild within 1d    locate in inflammatory, haemostatic;

-   identify SeqInflammatoryAugmentationPlateletFallMod as    InflammatoryAugmentationMod preceding PlateletsFallModerate within    1d locate in inflammatory, haemostatic;

-   identify SeqInflammatoryAugmentationPlateletFallSevere as    InflammatoryAugmentationSevere preceding PlateletsFallSevere within    1d locate in inflammatory, haemostatic;

-   identify SeqInflammatoryAugmentationPlateletFallProfound as    InflammatoryAugmentationProfound preceding PlateletsFallProfound    within 1d locate in inflammatory, haemostatic;

-   identify InflammatoryAugmentationPlateletLowOrFallMarginal as    InflammatoryAugmentationMarginal and PlateletsFallMarginal within 1d    locate in inflammatory, haemostatic;

-   identify InflammatoryAugmentationPlateletLowOrFallMild as    InflammatoryAugmentationMild and PlateletsFallMild within 1d locate    in inflammatory, haemostatic;

-   identify InflammatoryAugmentationPlateletLowOrFallMod as    InflammatoryAugmentationMod and PlateletsFallModerate within 1d    locate in inflammatory, haemostatic;

-   identify InflammatoryAugmentationPlateletLowOrFallSevere as    InflammatoryAugmentationSevere and PlateletsFallSevere within 1d    locate in inflammatory, haemostatic;

-   identify InflammatoryAugmentationPlateletLowOrFallProfound as    InflammatoryAugmentationProfound and PlateletsFallProfound within 1d    locate in inflammatory, haemostatic;    —Inflammation and Acid Base

-   identify SeqInflammationAndAcidosisMarginal as    InflammatoryAugmentationMarginal preceding AcidosisMarginal within    1d locate in inflammatory, acidbase;

-   identify SeqInflammationAndAcidosisMild as    InflammatoryAugmentationMild preceding AcidosisMild within 1d locate    in inflammatory, acidbase;

-   identify SeqInflammationAndAcidosisModerate as    InflammatoryAugmentationMod preceding AcidosisMod within 1d locate    in inflammatory, acidbase;

-   identify SeqInflammationAndAcidosisSevere as    InflammatoryAugmentationSevere preceding AcidosisSevere within 1d    locate in inflammatory, acidbase;

-   identify SeqInflammationAndAcidosisProfound as    InflammatoryAugmentationProfound preceding AcidosisProfound within    1d locate in inflammatory, acidbase;

-   identify InflammationAndAcidosisMarginal as    InflammatoryAugmentationMarginal and AcidosisMarginal within 1d    locate in inflammatory, acidbase;

-   identify InflammationAndAcidosisMild as InflammatoryAugmentationMild    and AcidosisMild within 1d locate in inflammatory, acidbase;

-   identify InflammationAndAcidosisMod as InflammatoryAugmentationMod    and AcidosisMod within 1d locate in inflammatory, acidbase;

-   identify InflammationAndAcidosisSevere as    InflammatoryAugmentationSevere and AcidosisSevere within 1d locate    in inflammatory, acidbase;

-   identify InflammationAndAcidosisProfound as    InflammatoryAugmentationProfound and AcidosisProfound within 1d    locate in inflammatory, acidbase;    —Inflammation and Metabolic

-   Identify InflammationAndAlbuminFallMarginal as    InflammatoryAugmentationMarginal and AlbuminFallMarginal within 2d    locate in inflammatory, metabolic;

-   Identify InflammationAndAlbuminFallMild as    InflammatoryAugmentationMild and AlbuminFallMild within 2d locate in    inflammatory, metabolic;

-   Identify InflammationAndAlbuminFallMod as    InflammatoryAugmentationMod and AlbuminFallModerate within 2d locate    in inflammatory, metabolic;

-   Identify InflammationAndAlbuminFallSevere as    InflammatoryAugmentationSevere and AlbuminFallSevere within 2d    locate in inflammatory, metabolic;

-   Identify InflammationAndAlbuminFallProfound as    InflammatoryAugmentationProfound and AlbuminFallProfound within 2d    locate in inflammatory, metabolic;

-   Identify SeqInflammationAndAlbuminFallMarginal as    InflammatoryAugmentationMarginal preceding AlbuminFallMarginal    within 2d locate in inflammatory, metabolic;

-   Identify SeqInflammationAndAlbuminFallMild as    InflammatoryAugmentationMild preceding AlbuminFallMild within 2d    locate in inflammatory, metabolic;

-   Identify SeqInflammationAndAlbuminFallMod as    InflammatoryAugmentationMod preceding AlbuminFallModerate within 2d    locate in inflammatory, metabolic;

-   Identify SeqInflammationAndAlbuminFallSevere as    InflammatoryAugmentationSevere preceding AlbuminFallSevere within 2d    locate in inflammatory, metabolic;

-   Identify SeqInflammationAndAlbuminFallProfound as    InflammatoryAugmentationProfound preceding AlbuminFallProfound    within 2d locate in inflammatory, metabolic;    —Haemostatic and Procalcitonin

-   identify SeqProcalcitoninPlateletFallMarginal as    ProcalcitoninRiseOrHighMarginal preceding PlateletsFallMarginal    within 1d locate in inflammatory, haemostatic;

-   identify SeqInflammationPlateletFallMild as    ProcalcitoninRiseOrHighMild preceding PlateletsFallMild within 1d    locate in inflammatory, haemostatic;

-   identify SeqProcalcitoninPlateletFallMod as    ProcalcitoninRiseOrHighMod preceding PlateletsFallModerate within 1d    locate in inflammatory, haemostatic;

-   identify SeqProcalcitoninPlateletFallSevere as    ProcalcitoninRiseOrHighSevere preceding PlateletsFallSevere within    1d locate in inflammatory, haemostatic;

-   identify SeqProcalcitoninPlateletFallProfound as    ProcalcitoninRiseOrHighProfound preceding PlateletsFallProfound    within 1d locate in inflammatory, haemostatic;

-   identify ProcalcitoninPlateletLowOrFallMarginal as    ProcalcitoninRiseOrHighMarginal and PlateletsFallMarginal within 1d    locate in inflammatory, haemostatic;

-   identify ProcalcitoninPlateletLowOrFallMild as    ProcalcitoninRiseOrHighMild and PlateletsFallMild within 1d locate    in inflammatory, haemostatic;

-   identify ProcalcitoninPlateletLowOrFallMod as    ProcalcitoninRiseOrHighMod and PlateletsFallModerate within 1d    locate in inflammatory, haemostatic;

-   identify ProcalcitoninPlateletLowOrFallSevere as    ProcalcitoninRiseOrHighSevere and PlateletsFallSevere within 1d    locate in inflammatory, haemostatic;

-   identify ProcalcitoninPlateletLowOrFallProfound as    ProcalcitoninRiseOrHighProfound and PlateletsFallProfound within 1d    locate in inflammatory, haemostatic;    —Acid Base and Procalcitonin

-   identify SeqProcalcitoninAcidosisMarginal as    ProcalcitoninRiseOrHighMarginal preceding AcidosisMarginal within 1d    locate in acidbase, inflammatory;

-   identify SeqProcalcitoninAcidosisMild as ProcalcitoninRiseOrHighMild    preceding AcidosisMarginal within 1d locate in acidbase,    inflammatory;

-   identify SeqProcalcitoninAcidosisMod as ProcalcitoninRiseOrHighMod    preceding AcidosisMod within 1d locate in acidbase, inflammatory;

-   identify SeqProcalcitoninAcidosisSevere as    ProcalcitoninRiseOrHighSevere preceding AcidosisSevere within 1d    locate in acidbase, inflammatory;

-   identify SeqProcalcitoninAcidosisProfound as    ProcalcitoninRiseOrHighProfound preceding AcidosisProfound within 1d    locate in acidbase, inflammatory;

-   identify ProcalcitoninAcidosisMarginal as    ProcalcitoninRiseOrHighMarginal and AcidosisMarginal within 1d    locate in acidbase, inflammatory;

-   identify ProcalcitoninAcidosisMild as ProcalcitoninRiseOrHighMild    and AcidosisMild within 1d locate in acidbase, inflammatory;

-   identify ProcalcitoninAcidosisMod as ProcalcitoninRiseOrHighMod and    AcidosisMod within 1d locate in acidbase, inflammatory;

-   identify ProcalcitoninAcidosisSevere as    ProcalcitoninRiseOrHighSevere and AcidosisSevere within 1d locate in    acidbase, inflammatory;

-   identify ProcalcitoninAcidosisProfound as    ProcalcitoninRiseOrHighProfound and AcidosisProfound within 1d    locate in acidbase, inflammatory;

-   identify SeqProcalcitoninLactateMarginal as    ProcalcitoninRiseOrHighMarginal preceding LactateRiseOrHighMarginal    within 1d locate in acidbase, inflammatory;

-   identify SeqProcalcitoninLactateMild as ProcalcitoninRiseOrHighMild    preceding LactateRiseOrHighMarginal within 1d locate in acidbase,    inflammatory;

-   identify SeqProcalcitoninLactateMod as ProcalcitoninRiseOrHighMod    preceding LactateRiseOrHighMod within 1d locate in acidbase,    inflammatory;

-   identify SeqProcalcitoninLactateSevere as    ProcalcitoninRiseOrHighSevere preceding LactateRiseOrHighSevere    within 1d locate in acidbase, inflammatory;

-   identify SeqProcalcitoninLactateProfound as    ProcalcitoninRiseOrHighProfound preceding LactateRiseOrHighProfound    within 1d locate in acidbase, inflammatory;

-   identify ProcalcitoninLactateMarginal as    ProcalcitoninRiseOrHighMarginal and LactateRiseOrHighMarginal within    1d locate in acidbase, inflammatory;

-   identify ProcalcitoninLactateMild as ProcalcitoninRiseOrHighMild and    LactateRiseOrHighMild within 1d locate in acidbase, inflammatory;

-   identify ProcalcitoninLactateMod as ProcalcitoninRiseOrHighMod and    LactateRiseOrHighMod within 1d locate in acidbase, inflammatory;

-   identify ProcalcitoninLactateSevere as ProcalcitoninRiseOrHighSevere    and LactateRiseOrHighSevere within 1d locate in acidbase,    inflammatory;

-   identify ProcalcitoninLactateProfound as    ProcalcitoninRiseOrHighProfound and LactateRiseOrHighProfound within    1d locate in acidbase, inflammatory;

-   identify ProcalcitoninBicarbFallMarginal as    ProcalcitoninRiseOrHighMarginal and BicarbFallMarginal within 1d    locate in acidbase, inflammatory;

-   identify ProcalcitoninBicarbFallMild as ProcalcitoninRiseOrHighMild    and BicarbFallMild within 1d locate in acidbase, inflammatory;

-   identify ProcalcitoninBicarbFallMod as ProcalcitoninRiseOrHighMod    and BicarbFallModerate within 1d locate in acidbase, inflammatory;

-   identify ProcalcitoninBicarbFallSevere as    ProcalcitoninRiseOrHighSevere and BicarbFallSevere within 1d locate    in acidbase, inflammatory;

-   identify ProcalcitoninBicarbFallProfound as    ProcalcitoninRiseOrHighProfound and BicarbFallProfound within 1d    locate in acidbase, inflammatory;

-   identify SeqProcalcitoninBicarbFallMarginal as    ProcalcitoninRiseOrHighMarginal preceding BicarbFallMarginal within    1d locate in acidbase, inflammatory;

-   identify SeqProcalcitoninFallOrLowBicarbMild as    ProcalcitoninRiseOrHighMild preceding BicarbFallMild within 1d    locate in acidbase, inflammatory;

-   identify SeqProcalcitoninBicarbFallMod as ProcalcitoninRiseOrHighMod    preceding BicarbFallModerate within 1d locate in acidbase,    inflammatory;

-   identify SeqProcalcitoninBicarbFallSevere as    ProcalcitoninRiseOrHighSevere preceding BicarbFallSevere within 1d    locate in acidbase, inflammatory;

-   identify SeqProcalcitoninBicarbFallProfound as    ProcalcitoninRiseOrHighProfound preceding BicarbFallProfound within    1d locate in acidbase, inflammatory;

-   identify ProcalcitoninFallOrLowBicarbMarginal as    ProcalcitoninRiseOrHighMarginal and BicarbFallOrLowMarginal within    1d locate in acidbase, inflammatory;

-   identify ProcalcitoninFallOrLowBicarbMild as    ProcalcitoninRiseOrHighMild and BicarbFallOrLowMild within 1d locate    in acidbase, inflammatory;

-   identify ProcalcitoninFallOrLowBicarbMod as    ProcalcitoninRiseOrHighMod and BicarbFallOrLowMod within 1d locate    in acidbase, inflammatory;

-   identify ProcalcitoninFallOrLowBicarbSevere as    ProcalcitoninRiseOrHighSevere and BicarbFallOrLowSevere within 1d    locate in acidbase, inflammatory;

-   identify ProcalcitoninFallOrLowBicarbProfound as    ProcalcitoninRiseOrHighProfound and BicarbFallOrLowProfound within    1d locate in acidbase, inflammatory;    —Cardiac

-   Identify HRHighOrRiseMarginal as HRHighMarginal or HRRiseMarginal    Locate in cardiac;

-   Identify HRHighOrRiseMild as HRHighMild or HRRiseMild Locate in    cardiac;

-   Identify HRHighOrRiseMod as HRHighModerate or HRRiseModerate Locate    in cardiac;

-   Identify HRHighOrRiseSevere as HRHighSevere or HRRiseSevere Locate    in cardiac;

-   Identify HRHighOrRiseProfound as HRHighProfound or HRRiseProfound    Locate in cardiac;

-   Identify BpSystolicLowOrFallMarginal as BpSystolicLowMarginal or    BpSystolicFallMarginal Locate in Cardiac;

-   Identify BpSystolicLowOrFallMild as BpSystolicLowMild or    BpSystolicFallMild Locate in Cardiac;

-   Identify BpSystolicLowOrFallMod as BpSystolicLowModerate or    BpSystolicFallModerate Locate in Cardiac;

-   Identify BpSystolicLowOrFallSevere as BpSystolicLowSevere or    BpSystolicFallSevere Locate in Cardiac;

-   Identify BpSystolicLowOrFallProfound as BpSystolicLowProfound or    BpSystolicFallProfound Locate in Cardiac;

-   Identify PDHRandBpSystolicMarginal as HRHighOrRiseMarginal and    BpSystolicLowOrFallMarginal within 1d Locate in cardiac;

-   Identify PDHRandBpSystolicMild as HRHighOrRiseMild and    BpSystolicLowOrFallMild within 1d Locate in cardiac;

-   Identify PDHRandBpSystolicMod as HRHighOrRiseMod and    BpSystolicLowOrFallMod within 1d Locate in cardiac;

-   Identify PDHRandBpSystolicSevere as HRHighOrRiseSevere and    BpSystolicLowOrFallSevere within 1d Locate in cardiac;

-   Identify PDHRandBpSystolicProfound as HRHighOrRiseProfound and    BpSystolicLowOrFallProfound within 1d Locate in cardiac;    —Cardiac/Respiratory

-   Identify SPO2HRMild as HRHighOrRiseMarginal and    SaO2LowOrFallMarginal within 1d Locate in respiratory;

-   Identify SPO2HRMild_duplicated as HRHighOrRiseMild and    SaO2LowOrFallMild within 1d Locate in respiratory;

-   Identify SPO2HRMod as HRHighOrRiseMod and SaO2LowOrFallMod within 1d    Locate in respiratory;

-   Identify SPO2HRSevere as HRHighOrRiseSevere and SaO2LowOrFallSevere    within 1d Locate in respiratory;

-   Identify SPO2HRProfound as HRHighOrRiseProfound and    SaO2LowOrFallProfound within 1d Locate in respiratory;    —Temp/Cardiac/Respiratory/Inflammation CONY Convergence or Coherence

-   Identify CONVHighHRRRMarginal as HRHighMarginal and    RespiratoryRateHighMarginal within 1d Locate in respiratory,    cardiac;

-   Identify CONVHighHRRRMild as HRHighMild and RespiratoryRateHighMild    within 1d Locate in respiratory, cardiac;

-   Identify CONVHighHRRRMod as HRHighModerate and    RespiratoryRateHighModerate within 1d Locate in respiratory,    cardiac;

-   Identify CONVHighHRRRSevere as HRHighSevere and    RespiratoryRateHighSevere within 1d Locate in respiratory, cardiac;

-   Identify CONVHighHRRRProfound as HRHighProfound and    RespiratoryRateHighProfound within 1d Locate in respiratory,    cardiac;

-   Identify CONVHighHRtempRRMarginal as CONVHighHRRRMarginal and    TemperatureFHighMarginal within 1d Locate in respiratory, cardiac,    inflammatory;

-   Identify CONVHighHRtempRRMild as CONVHighHRRRMild and    TemperatureFHighMild within 1d Locate in respiratory, cardiac,    inflammatory;

-   Identify CONVHighHRtempRRMod as CONVHighHRRRMod and    TemperatureFHighModerate and RespiratoryRateHighModerate within 1d    Locate in respiratory, cardiac, inflammatory;

-   Identify CONVHighHRtempRRSevere as CONVHighHRRRSevere and    TemperatureFHighSevere and RespiratoryRateHighSevere within 1d    Locate in respiratory, cardiac, inflammatory;

-   Identify CONVHighHRtempRRProfound as CONVHighHRRRProfound and    TemperatureFHighProfound and RespiratoryRateHighProfound within 1d    Locate in respiratory, cardiac, inflammatory;

-   Identify CONVHighHRtempRRInflammationMarginal as    CONVHighHRtempRRMarginal and InflammatoryAugmentationMarginal within    1d Locate in respiratory, cardiac, inflammatory;

-   Identify CONVHighHRtempRRInflammationMild as CONVHighHRtempRRMild    and InflammatoryAugmentationMild within 1d Locate in respiratory,    cardiac, inflammatory;

-   Identify CONVHighHRtempRRInflammationMod as CONVHighHRtempRRMod and    InflammatoryAugmentationMod within 1d Locate in respiratory,    cardiac, inflammatory;

-   Identify CONVHighHRtempRRInflammationSevere as    CONVHighHRtempRRSevere and InflammatoryAugmentationSevere within 1d    Locate in respiratory, cardiac, inflammatory;

-   Identify CONVHighHRtempRRInflammationProfound as    CONVHighHRtempRRProfound and InflammatoryAugmentationProfound within    1d Locate in respiratory, cardiac, inflammatory;

-   Identify CONVHighHRtempRRInflammationCumMarginal as    CONVHighHRtempRRMarginal and NeutrophilAndBandAndTempMarginal within    1d Locate in respiratory, cardiac,

-   inflammatory;

-   Identify CONVHighHRtempRRInflammationCumMild as CONVHighHRtempRRMild    and NeutrophilAndBandAndTempMild within 1d Locate in respiratory,    cardiac, inflammatory;

-   Identify CONVHighHRtempRRInflammationCumMod as CONVHighHRtempRRMod    and NeutrophilAndBandAndTempMod within 1d Locate in respiratory,    cardiac, inflammatory;

-   Identify CONVHighHRtempRRInflammationCumSevere as    CONVHighHRtempRRSevere and NeutrophilAndBandAndTempSevere within 1d    Locate in respiratory, cardiac, inflammatory;

-   Identify CONVHighHRtempRRInflammationCumProfound as    CONVHighHRtempRRProfound and NeutrophilAndBandAndTempProfound within    1d Locate in respiratory, cardiac, inflammatory;

-   Identify PDHHighHRRRBpLowOrFallSystolicMarginal as    CONVHighHRRRMarginal and BpSystolicLowOrFallMarginal within 1d    Locate in respiratory, cardiac;

-   Identify PDHHighHRRRBpLowOrFallSystolicMild as CONVHighHRRRMild and    BpSystolicLowOrFallMild within 1d Locate in respiratory, cardiac;

-   Identify PDHHighHRRRBpLowOrFallSystolicModerate as CONVHighHRRRMod    and BpSystolicLowOrFallMod within 1d Locate in respiratory, cardiac;

-   Identify PDHHighHRRRBpLowOrFallSystolicSevere as CONVHighHRRRSevere    and BpSystolicLowOrFallSevere within 1d Locate in respiratory,    cardiac;

-   Identify PDHHighHRRRBpLowOrFallSystolicProfound as    CONVHighHRRRProfound and BpSystolicLowOrFallProfound within 1d    Locate in respiratory, cardiac;

-   Identify PDHighHRtempRRInflammationlowBPMarginal as    CONVHighHRtempRRInflammationMarginal and BpSystolicLowOrFallMarginal    within 1d Locate in respiratory, cardiac, inflammatory; Identify    PDHighHRtempRRInflammationlowBPMild as    CONVHighHRtempRRInflammationMild and BpSystolicLowOrFallMild within    1d Locate in

-   respiratory, cardiac, inflammatory;

-   Identify PDHighHRtempRRInflammationlowBPMod as    CONVHighHRtempRRInflammationMod and BpSystolicLowOrFallMod within 1d    Locate in respiratory, cardiac, inflammatory;

-   Identify PDHighHRtempRRInflammationlowBPSevere as    CONVHighHRtempRRInflammationSevere and BpSystolicLowOrFallSevere    within 1d Locate in respiratory, cardiac, inflammatory;

-   Identify PDHighHRtempRRInflammationlowBPProfound as    CONVHighHRtempRRInflammationProfound and BpSystolicLowOrFallProfound    within 1d Locate in respiratory, cardiac, inflammatory;    —Pathophysiologic Divergence or Decoherence of Acidosis, SPO2

-   Identify PDAcidosisSaO2Marginal as AcidosisMarginal and    SaO2LowOrFallMarginal within 1d Locate in respiratory, acidbase;

-   Identify PDAcidosisSaO2Mild as AcidosisMild and SaO2LowOrFallMild    within 1d Locate in respiratory, acidbase; Identify    PDAcidosisSaO2Mod as AcidosisMod and SaO2LowOrFallMod within 1d    Locate in

-   respiratory, acidbase;

-   Identify PDAcidosisSaO2Severe as AcidosisSevere and    SaO2LowOrFallSevere within 1d Locate in respiratory, acidbase;

-   Identify PDAcidosisSaO2Profound as AcidosisProfound and    SaO2LowOrFallProfound within 1d Locate in respiratory, acidbase;

-   Identify PDLactateSaO2Marginal as LactateRiseOrHighMarginal and    SaO2LowOrFallMarginal within 1d Locate in respiratory, acidbase;

-   Identify PDLactateSaO2Mild as LactateRiseOrHighMild and    SaO2LowOrFallMild within 1d Locate in respiratory, acidbase;

-   Identify PDLactateSaO2Mod as LactateRiseOrHighMod and    SaO2LowOrFallMod within 1d Locate in respiratory, acidbase;

-   Identify PDLactateSaO2Severe as LactateRiseOrHighSevere and    SaO2LowOrFallSevere within 1d Locate in respiratory, acidbase;

-   Identify PDLactateSaO2Profound as LactateRiseOrHighProfound and    SaO2LowOrFallProfound within 1d Locate in respiratory, acidbase;

-   Identify CONVAcidosisRRMarginal as AcidosisMarginal and    RespiratoryRateHighMarginal within 1d Locate in respiratory,    cardiac;

-   Identify CONVAcidosisRRMild as AcidosisMild and    RespiratoryRateHighMild within 1d Locate in respiratory, cardiac;

-   Identify CONVAcidosisRRMod as AcidosisMod and    RespiratoryRateHighModerate within 1d Locate in respiratory,    cardiac;

-   Identify CONVAcidosisRRSevere as AcidosisSevere and    RespiratoryRateHighSevere within 1d Locate in respiratory, cardiac;

-   Identify CONVAcidosisRRProfound as AcidosisProfound and    RespiratoryRateHighProfound within 1d Locate in respiratory,    cardiac;

-   Identify PDAcidosisOrLactateSaO2Marginal as PDAcidosisSaO2Marginal    or PDLactateSaO2Marginal locate in respiratory, acidbase;

-   Identify PDAcidosisOrLactateSaO2Mild as PDAcidosisSaO2Mild or    PDLactateSaO2Mild locate in respiratory, acidbase;

-   Identify PDAcidosisOrLactateSaO2Mod as PDAcidosisSaO2Mod or    PDLactateSaO2Mod locate in respiratory, acidbase;

-   Identify PDAcidosisOrLactateSaO2Severe as PDAcidosisSaO2Severe or    PDLactateSaO2Severe locate in respiratory, acidbase;

-   Identify PDAcidosisOrLactateSaO2Profound as PDAcidosisSaO2Profound    or PDLactateSaO2Profound locate in respiratory, acidbase;    —Pathophysiologic Divergence or Decoherence of Acidosis, BP

-   Identify PDAcidosisLowOrFallBP as AcidosisMarginal and    BpSystolicLowOrFallMarginal within 1d Locate in acidbase, cardiac;

-   Identify PDAcidosisLowOrFallBP_Duplicated as AcidosisMild and    BpSystolicLowOrFallMild within 1d Locate in acidbase, cardiac;

-   Identify PDAcidosisLowOrFallBP_Duplicated2 as AcidosisMod and    BpSystolicLowOrFallMod within 1d Locate in acidbase, cardiac;

-   Identify PDAcidosisLowOrFallBP_Duplicated3 as AcidosisSevere and    BpSystolicLowOrFallSevere within 1d Locate in acidbase, cardiac;

-   Identify PDAcidosisLowOrFallBP_Duplicated4 as AcidosisProfound and    BpSystolicLowOrFallProfound within 1d Locate in acidbase, cardiac;

-   Identify PDAcidosisSPO2InflammationMarginal as    PDAcidosisSaO2Marginal and InflammatoryAugmentationMarginal within    1d Locate in acidbase, respiratory, inflammatory;

-   Identify PDAcidosisSPO2InflammationMild as PDAcidosisSaO2Mild and    InflammatoryAugmentationMild within 1d Locate in acidbase,    respiratory, inflammatory;

-   Identify PDAcidosisSPO2InflammationMod as PDAcidosisSaO2Mod and    InflammatoryAugmentationMod within 1d Locate in acidbase,    respiratory, inflammatory;

-   Identify PDAcidosisSPO2InflammationSevere as PDAcidosisSaO2Severe    and InflammatoryAugmentationSevere within 1d Locate in acidbase,    respiratory, inflammatory;

-   Identify PDAcidosisSPO2InflammationProfound as    PDAcidosisSaO2Profound and InflammatoryAugmentationProfound within    1d Locate in acidbase, respiratory, inflammatory;

-   Identify PDAcidosisSPO2InflammationCumMarginal as    PDAcidosisSaO2Marginal and NeutrophilAndBandAndTempMarginal within    1d Locate in acidbase, respiratory, inflammatory;

-   Identify PDAcidosisSPO2InflammationCumMild as PDAcidosisSaO2Mild and    NeutrophilAndBandAndTempMild within 1d Locate in acidbase,    respiratory, inflammatory;

-   Identify PDAcidosisSPO2InflammationCumMod as PDAcidosisSaO2Mod and    NeutrophilAndBandAndTempMod within 1d Locate in acidbase,    respiratory, inflammatory;

-   Identify PDAcidosisSPO2InflammationCumSevere as PDAcidosisSaO2Severe    and NeutrophilAndBandAndTempSevere within 1d Locate in acidbase,    respiratory, inflammatory;

-   Identify PDAcidosisSPO2InflammationCumProfound as    PDAcidosisSaO2Profound and NeutrophilAndBandAndTempProfound within    1d Locate in acidbase, respiratory, inflammatory;

-   Identify PDLactateSPO2InflammationMarginal as PDLactateSaO2Marginal    and InflammatoryAugmentationMarginal within 1d Locate in acidbase,    respiratory, inflammatory;

-   Identify PDLactateSPO2InflammationMild as PDLactateSaO2Mild and    InflammatoryAugmentationMild within 1d Locate in acidbase,    respiratory, inflammatory;

-   Identify PDLactateSPO2InflammationMod as PDLactateSaO2Mod and    InflammatoryAugmentationMod within 1d Locate in acidbase,    respiratory, inflammatory;

-   Identify PDLactateSPO2InflammationSevere as PDLactateSaO2Severe and    InflammatoryAugmentationSevere within 1d Locate in acidbase,    respiratory, inflammatory;

-   Identify PDLactateSPO2InflammationProfound as PDLactateSaO2Profound    and InflammatoryAugmentationProfound within 1d Locate in acidbase,    respiratory, inflammatory;

-   Identify PDLactateSPO2InflammationCumMarginal as    PDLactateSaO2Marginal and NeutrophilAndBandAndTempMarginal within 1d    Locate in acidbase, respiratory, inflammatory;

-   Identify PDLactateSPO2InflammationCumMild as PDLactateSaO2Mild and    NeutrophilAndBandAndTempMild within 1d Locate in acidbase,    respiratory, inflammatory;

-   Identify PDLactateSPO2InflammationCumMod as PDLactateSaO2Mod and    NeutrophilAndBandAndTempMod within 1d Locate in acidbase,    respiratory, inflammatory;

-   Identify PDLactateSPO2InflammationCumSevere as PDLactateSaO2Severe    and NeutrophilAndBandAndTempSevere within 1d Locate in acidbase,    respiratory, inflammatory;

-   Identify PDLactateSPO2InflammationCumProfound as    PDLactateSaO2Profound and NeutrophilAndBandAndTempProfound within 1d    Locate in acidbase, respiratory, inflammatory;

-   Identify HRHighorRRHighMarginal as HRHighMarginal or    RespiratoryRateHighMarginal Locate in respiratory, cardiac;

-   Identify HRHighorRRHighMild as HRHighMild or RespiratoryRateHighMild    Locate in respiratory, cardiac;

-   Identify HRHighorRRHighMod as HRHighModerate or    RespiratoryRateHighModerate Locate in respiratory, cardiac;

-   Identify HRHighorRRHighSevere as HRHighSevere or    RespiratoryRateHighSevere Locate in respiratory, cardiac;

-   Identify HRHighorRRHighProfound as HRHighProfound or    RespiratoryRateHighProfound Locate in respiratory, cardiac;    —Renal Failure

-   identify CreatinineRiseOrHighMarginal as CreatinineRiseMarginal or    CreatinineHighMarginal locate in renal;

-   identify CreatinineRiseOrHighMild as CreatinineRiseMild or    CreatinineHighMild locate in renal;

-   identify CreatinineRiseOrHighMod as CreatinineRiseModerate or    CreatinineHighModerate locate in renal;

-   identify CreatinineRiseOrHighSevere as CreatinineRiseSevere or    CreatinineHighSevere locate in renal;

-   identify CreatinineRiseOrHighProfound as CreatinineRiseProfound or    CreatinineHighProfound locate in renal;    —SIRS

-   Identify SIRSMarginal as InflammatoryAugmentationMarginal and    HRHighorRRHighMarginal within 1d locate in inflammatory;

-   Identify SIRSMild as InflammatoryAugmentationMild and    HRHighorRRHighMild within 1d locate in inflammatory;

-   Identify SIRSMod as InflammatoryAugmentationMod and    HRHighorRRHighMod within 1d locate in inflammatory;

-   Identify SIRSSevere as InflammatoryAugmentationSevere and    HRHighorRRHighSevere within 1d locate in inflammatory;

-   Identify SIRSProfound as InflammatoryAugmentationProfound and    HRHighorRRHighProfound within 1d locate in inflammatory;    —InflammatoryAugmentation and Increase or High Acid

-   Identify InflammatoryAugmentationandAcidMarginal as    InflammatoryAugmentationMarginal and    AcidosisOrBicarbFallorLoworLactateMarginal within 1d locate in    inflammatory, acidbase;

-   Identify InflammatoryAugmentationandAcidMild as SIRSMild and    InflammatoryAugmentationMild within 1d locate in inflammatory,    acidbase;

-   Identify InflammatoryAugmentationandAcidMod as SIRSMod and    InflammatoryAugmentationMod within 1d locate in inflammatory,    acidbase;

-   Identify InflammatoryAugmentationandAcidSevere as SIRSSevere and    InflammatoryAugmentationSevere within 1d locate in inflammatory,    acidbase;

-   Identify InflammatoryAugmentationandAcidProfound as SIRSProfound and    InflammatoryAugmentationProfound within 1d locate in inflammatory,    acidbase;    —InflammatoryAugmentation and Low or Fall Platelets

-   Identify InflammatoryAugmentationandPlateletsLoworFallMarginal as    InflammatoryAugmentationMarginal and PlateletLowOrFallMarginal    within 1d locate in inflammatory, acidbase;

-   Identify InflammatoryAugmentationandPlateletsLoworFallMild as    InflammatoryAugmentationMild and PlateletLowOrFallMild within 1d    locate in inflammatory, acidbase;

-   Identify InflammatoryAugmentationandPlateletsLoworFallMod as    InflammatoryAugmentationMod and PlateletLowOrFallModerate within 1d    locate in inflammatory, acidbase;

-   Identify InflammatoryAugmentationandPlateletsLoworFallSevere as    InflammatoryAugmentationSevere and PlateletLowOrFallSevere within 1d    locate in inflammatory, acidbase;

-   Identify InflammatoryAugmentationandPlateletsLoworFallProfound as    InflammatoryAugmentationProfound and PlateletLowOrFallSevere within    1d locate in inflammatory, acidbase;    —InflammatoryAugmentation and Low or Fall Calcium

-   Identify InflammatoryAugmentationandCalciumMarginal as    InflammatoryAugmentationMarginal and FallorLowCalciumMarginal within    1d locate in inflammatory, acidbase;

-   Identify InflammatoryAugmentationandCalciumMild as    InflammatoryAugmentationMild and FallorLowCalciumMild within 1d    locate in inflammatory, acidbase;

-   Identify InflammatoryAugmentationandCalciumMod as    InflammatoryAugmentationMod and FallorLowCalciumMod within 1d locate    in inflammatory, acidbase;

-   Identify InflammatoryAugmentationandCalciumSevere as    InflammatoryAugmentationSevere and FallorLowCalciumSevere within 1d    locate in inflammatory, acidbase;

-   Identify InflammatoryAugmentationandCalciumProfound as    InflammatoryAugmentationProfound and FallorLowCalciumProfound within    1d locate in inflammatory, acidbase;    —InflammatoryAugmentation and High or Rise Creatinine

-   Identify InflammatoryAugmentationandCreatinineMarginal as    InflammatoryAugmentationMarginal and CreatinineRiseOrHighMarginal    within 1d locate in inflammatory, Renal;

-   Identify InflammatoryAugmentationandCreatinineFailureMild as    InflammatoryAugmentationMild and CreatinineRiseOrHighMild within 1d    locate in inflammatory, Renal;

-   Identify InflammatoryAugmentationandCreatinineMod as    InflammatoryAugmentationMod and CreatinineRiseOrHighMod within 1d    locate in inflammatory, Renal;

-   Identify InflammatoryAugmentationandCreatinineSevere as    InflammatoryAugmentationSevere and CreatinineRiseOrHighSevere within    1d locate in inflammatory, Renal;

-   Identify InflammatoryAugmentationandCreatinineProfound as    InflammatoryAugmentationProfound and CreatinineRiseOrHighProfound    within 1d locate in inflammatory, Renal;    —InflammatoryAugmentation and Fall or Low Albumin

-   Identify InflammatoryAugmentationandAlbuminMarginal as    InflammatoryAugmentationMarginal and AlbuminFallMarginal within 1d    locate in inflammatory, Renal;

-   Identify InflammatoryAugmentationandAlbuminFailureMild as    InflammatoryAugmentationMild and AlbuminFallMild within 1d locate in    inflammatory, Renal;

-   Identify InflammatoryAugmentationandAlbuminMod as    InflammatoryAugmentationMod and AlbuminFallModerate within 1d locate    in inflammatory, Renal;

-   Identify InflammatoryAugmentationandAlbuminSevere as    InflammatoryAugmentationSevere and AlbuminFallSevere within 1d    locate in inflammatory, Renal;

-   Identify InflammatoryAugmentationandAlbuminProfound as    InflammatoryAugmentationProfound and AlbuminFallProfound within 1d    locate in inflammatory, Renal;    —SIRS and Acid

-   Identify SIRSandAcidMarginal as SIRSMarginal and    AcidosisOrBicarbFallorLoworLactateMarginal within 1d locate in    inflammatory, acidbase;

-   Identify SIRSandAcidMild as SIRSMild and    AcidosisOrBicarbFallorLoworLactateMild within 1d locate in    inflammatory, acidbase;

-   Identify SIRSandAcidMod as SIRSMod and    AcidosisOrBicarbFallorLoworLactateMod within 1d locate in    inflammatory, acidbase;

-   Identify SIRSandAcidSevere as SIRSSevere and    AcidosisOrBicarbFallorLoworLactateSevere within 1d locate in    inflammatory, acidbase;

-   Identify SIRSandAcidProfound as SIRSProfound and    AcidosisOrBicarbFallorLoworLactateProfound within 1d locate in    inflammatory, acidbase;    —SIRS and Low or Fall Platelets

-   Identify SIRSandPlateletsLoworFallMarginal as SIRSMarginal and    PlateletLowOrFallMarginal within 1d locate in inflammatory,    acidbase;

-   Identify SIRSandPlateletsLoworFallMild as SIRSMild and    PlateletLowOrFallMild within 1d locate in inflammatory, acidbase;

-   Identify SIRSandPlateletsLoworFallMod as SIRSMod and    PlateletLowOrFallModerate within 1d locate in inflammatory,    acidbase;

-   Identify SIRSandPlateletsLoworFallSevere as SIRSSevere and    PlateletLowOrFallSevere within 1d locate in inflammatory, acidbase;

-   Identify SIRSandPlateletsLoworFallProfound as SIRSProfound and    PlateletLowOrFallProfound within 1d locate in inflammatory,    acidbase;    —SIRS and Low or Fall Calcium

-   Identify SIRSandAcidMarginal_Duplicated as SIRSMarginal and    FallorLowCalciumMarginal within 1d locate in inflammatory, acidbase;

-   Identify SIRSandAcidMild_Duplicated as SIRSMild and    FallorLowCalciumMild within 1d locate in inflammatory, acidbase;

-   Identify SIRSandAcidMod_Duplicated as SIRSMod and    FallorLowCalciumMod within 1d locate in inflammatory, acidbase;

-   Identify SIRSandAcidSevere_Duplicated as SIRSSevere and    FallorLowCalciumSevere within 1d locate in inflammatory, acidbase;

-   Identify SIRSandAcidProfound_Duplicated as SIRSProfound and    FallorLowCalciumProfound within 1d locate in inflammatory, acidbase;    —SIRS and High or Rise Creatinine

-   Identify SIRSandCreatinineMarginal as SIRSMarginal and    CreatinineRiseOrHighMarginal within 1d locate in inflammatory,    Renal;

-   Identify SIRSandCreatinineMild as SIRSMild and    CreatinineRiseOrHighMild within 1d locate in inflammatory, Renal;

-   Identify SIRSandCreatinineMod as SIRSMod and CreatinineRiseOrHighMod    within 1d locate in inflammatory, Renal;

-   Identify SIRSandCreatinineSevere as SIRSSevere and    CreatinineRiseOrHighSevere within 1d locate in inflammatory, Renal;

-   Identify SIRSandCreatinineProfound as SIRSProfound and    CreatinineRiseOrHighProfound within 1d locate in inflammatory,    Renal;    —SIRS and Fall or Low Albumin

-   Identify SIRSandAlbuminMarginal as SIRSMarginal and    AlbuminFallMarginal within 1d locate in inflammatory, Renal;

-   Identify SIRSandAlbuminFailureMild as SIRSMild and AlbuminFallMild    within 1d locate in inflammatory, Renal;

-   Identify SIRSandAlbuminMod as SIRSMod and AlbuminFallModerate within    1d locate in inflammatory, Renal;

-   Identify SIRSandAlbuminSevere as SIRSSevere and AlbuminFallSevere    within 1d locate in inflammatory, Renal;

-   Identify SIRSandAlbuminProfound as SIRSProfound and    AlbuminFallProfound within 1d locate in inflammatory, Renal;    —SIRS

-   Identify SIRSandPDAcidosisOrLactateSaO2Marginal as SIRSMarginal and    PDAcidosisOrLactateSaO2Marginal within 1d locate in inflammatory,    Respiratory;

-   Identify SIRSandPDAcidosisOrLactateSaO2Mild as SIRSMild and    PDAcidosisOrLactateSaO2Mild within 1d locate in inflammatory,    Respiratory;

-   Identify SIRSandPDAcidosisOrLactateSaO2Mod as SIRSMod and    PDAcidosisOrLactateSaO2Mod within 1d locate in inflammatory,    Respiratory;

-   Identify SIRSandPDAcidosisOrLactateSaO2Severe as SIRSSevere and    PDAcidosisOrLactateSaO2Severe within 1d locate in inflammatory,    Respiratory;

-   Identify SIRSandPDAcidosisOrLactateSaO2Profound as SIRSProfound and    PDAcidosisOrLactateSaO2Profound within 1d locate in inflammatory,    Respiratory;

-   Identify SIRSandPDSPO2RRMarginal as SIRSMarginal and    PDSPO2RRMarginal within 1d locate in inflammatory, Respiratory;

-   Identify SIRSandPDSPO2RRMild as SIRSMild and PDSPO2RRMild within 1d    locate in inflammatory, Respiratory;

-   Identify SIRSandPDSPO2RRMod as SIRSMod and PDSPO2RRMod within 1d    locate in inflammatory, Respiratory;

-   Identify SIRSandPDSPO2RRSevere as SIRSSevere and PDSPO2RRSevere    within 1d locate in inflammatory, Respiratory;

-   Identify SIRSandPDSPO2RRProfound as SIRSProfound and    PDSPO2RRProfound within 1d locate in inflammatory, Respiratory;    —Identify SIRS and Respiratory Failure

-   Identify SIRSandRespFailureMarginal as    SIRSandPDAcidosisOrLactateSaO2Marginal or SIRSandPDSPO2RRMarginal    locate in inflammatory, Respiratory;

-   Identify SIRSandRespFailureMild as    SIRSandPDAcidosisOrLactateSaO2Mild or SIRSandPDSPO2RRMild locate in    inflammatory, Respiratory;

-   Identify SIRSandRespFailureMod as SIRSandPDAcidosisOrLactateSaO2Mod    or SIRSandPDSPO2RRMod locate in inflammatory, Respiratory;

-   Identify SIRSandRespFailureSevere as    SIRSandPDAcidosisOrLactateSaO2Severe or SIRSandPDSPO2RRSevere locate    in inflammatory, Respiratory;

-   Identify SIRSandRespFailureProfound as    SIRSandPDAcidosisOrLactateSaO2Profound or SIRSandPDSPO2RRProfound    locate in inflammatory, Respiratory;    —PAID Parenteral Antibiotic Indicating Disorder    Identify Sepsis as    -   SIRSMarginal or    -   SIRSMild        -   locate in inflammatory        -   indicate PAID;            Identify SepsisModerate as    -   SIRSMod or        -   InflammatoryAugmentationMod or        -   InflammatoryAugmentationandPlateletsLoworFallMild or        -   InflammatoryAugmentationandCalciumMod or        -   SIRSandAlbuminMod or        -   SIRSandCreatinineMild        -   locate in inflammatory        -   indicate PAID;            Identify SepsisSevere as    -   SIRSSevere or        -   InflammatoryAugmentationSevere or        -   SIRSandRespFailureMild or        -   InflammatoryAugmentationandAcidMod or        -   SIRSandCreatinineMod or        -   InflammatoryAugmentationandPlateletsLoworFallMod or        -   NeutrophilFailureMod or        -   SIRSandAcidMod        -   locate in inflammatory        -   indicate PAID, Sepsis;            Identify SepsisProfound as    -   SIRSSevere or        -   InflammatoryAugmentationProfound or        -   SIRSandRespFailureMod or        -   InflammatoryAugmentationandAcidSevere or        -   SIRSandCreatinineSevere or        -   InflammatoryAugmentationandPlateletsLoworFallSevere            or        -   NeutrophilFailureSevere or        -   SIRSandAcidMod        -   locate in inflammatory        -   indicate PAID, Sepsis;            Identify SepsisPromptResuscitationRequired as    -   SIRSandRespFailureSevere or        -   InflammatoryAugmentationandAcidProfound or        -   SIRSandAcidSevere        -   locate in inflammatory        -   indicate PAID, Sepsis;

What is claimed is:
 1. A real-time patient monitoring system comprising:a real-time patient monitor communicatively coupled to a plurality ofmeasurement devices, the patient monitor having a display device, amemory to store instructions, and one or more processors communicativelycoupled to the memory and the display; and a storage device incommunication with the patient monitor configured to store historicalphysiologic and laboratory data values about a plurality ofphysiological systems of a patient; wherein the instructions, whenexecuted by one of the one or more processors, cause the patientmonitoring system to receive in real-time a plurality of time series,each of the time series being biologic particle density values of abiologic particle type associated with a patient, generate a pluralityof perturbations by identifying changes in the biological particledensity values of the plurality of time series, determine, for eachperturbation, a plurality of properties of the perturbation, wherein theproperties include at least one of a slope, a magnitude, a percentchange, a change duration, a minimum, a maximum, and a change relativeto a normal range for the biologic particle density of the biologicparticle type, assign a severity value to each determined property ofeach perturbation, wherein the severity values correspond to theseverity of the determined property with respect to at least oneclinical condition, generate in real time a plurality of sequentialseverity profiles over time for each clinical condition, each severityprofile being responsive to severity values of the properties of theperturbations associated with the clinical condition; generate as anearly warning a first dynamic image based on the plurality of sequentialseverity profiles, the first dynamic image having a first time series ofa plurality of first images, each first image of the plurality of firstimages having a cell corresponding to a status of a clinical conditionof the patient at a point-in-time wherein a color distribution of thecell corresponds to at least one of the plurality of sequential severityprofiles, and present in real-time, on a map presented at the displaydevice, one of the plurality of first images of the first dynamic image,the map comprising a plurality of map regions, each map region of theplurality of map regions corresponding to a physiological system of aplurality of physiological systems of the patient.
 2. The patientmonitoring system of claim 1, wherein the instructions, when executed,further cause the patient monitoring system to generate a second dynamicimage comprising a second time series of a plurality of second images,each second image generated based on the plurality of sequentialseverity profiles and visually depicting a status of the clinicalcondition at a point-in-time; present, along a time axis presented atthe display device, one or more second images of the plurality of secondimages of the second dynamic, and indicate which one of the plurality ofsecond images displayed on the time axis corresponds to one of the firstimages of the plurality of first images of the first dynamic image thatis currently displayed on the map.
 3. The patient monitoring system ofclaim 2, wherein an indication of a patient treatment event ispositioned along the time axis.
 4. The patient monitoring system ofclaim 1, wherein: the first dynamic image is one of a plurality ofdynamic images generated for a plurality of patients, each dynamic imagevisually depicting a status of one of at least one clinical condition atone of the plurality of patients; and each of the plurality of dynamicimages are presented simultaneously in a trellis display.
 5. The patientmonitoring system as in claim 4 in which the plurality of dynamic imagesare sorted at the trellis display by severity of the clinical condition.6. The patient monitoring system as in claim 1 wherein a histogram isgenerated and presented adjacent the first dynamic image and individualfirst images of the first dynamic image are presented on the map inresponse to receipt of user input selecting individual points-in-time onthe histogram.
 7. The patient monitoring system as in claim 3 in whichthe second dynamic image comprises an indication of a relationshipbetween the patient treatment event and one of the plurality of secondimages of the second dynamic image.
 8. The patient monitoring system asin claim 2 in which one of the first images of the first dynamic imageand one of the second images of the second dynamic image are eachassociated with a point-in-time, and the first image and the secondimage associated with the point-in-time are each presented in responseto receipt of user input selecting the point-in-time.
 9. The patientmonitoring system of claim 1 wherein the clinical condition is sepsis.10. The patient monitoring system of claim 1, wherein: the instructions,when executed, further cause the patient monitoring system to animatethe first dynamic image by presenting in sequence at least two firstimages of the plurality of first images.
 11. The patient monitoringsystem of claim 1, wherein: the instructions, when executed, cause thepatient monitoring system to generate a severity profile of the one ormore sequential severity profiles by executing a script associated witha clinical sub-condition, the script configured to generate the severityprofile by aggregating at least two sequential severity profilesgenerated for at least two perturbations associated with the clinicalsub-condition.
 12. The patient monitoring system of claim 1, wherein:the instructions, when executed, cause the patient monitoring system togenerate a severity profile of the one or more sequential severityprofiles by generating a first severity profile associated with a firstclinical sub-condition, generating a second severity profile associatedwith a second clinical sub-condition, and aggregating the first severityprofile and the second severity profile to obtain the severity profile.13. A real-time patient monitoring system comprising: a real-timepatient monitor communicatively coupled to a plurality of measurementdevices, the patient monitor having a display device, a memory to storeinstructions, and one or more processors communicatively coupled to thememory and the display; and a storage device in communication with thepatient monitor configured to store historical physiologic andlaboratory data values about a plurality of physiological systems of apatient; wherein the instructions, when executed by the one or moreprocessors, cause the patient monitoring system to receive in real-timea plurality of time series, each of the time series being biologicparticle density values of a biologic particle type associated with apatient, generate a plurality of perturbations by identifying changes inthe biological particle density values of the plurality of time series,determine, for each perturbation, a plurality of properties of theperturbation, wherein the properties include at least one of a slope, amagnitude, a percent change, a change duration, a minimum, a maximum,and a change relative to a normal range for the biologic particledensity, assign a severity value to each determined property of eachperturbation, wherein the severity values correspond to the severity ofthe determined property with respect to at least one clinical condition,generate in real-time a plurality of sequential severity profiles overtime for each clinical condition, each severity profile being responsiveto severity values of the properties of the perturbations associatedwith the physiological system, generate as an early warning, based onthe plurality of sequential severity profiles, a dynamic imagecomprising a time series of a plurality of images, each image of theplurality of images comprising a cell corresponding to a status of aclinical condition at a point-in-time of a plurality of points-in-timewherein a color distribution of the cell corresponds to at least one ofthe plurality of sequential severity profiles, determine, based on thedata, a potential future status of the clinical condition and generate,based on the data, a visual indication of the potential future status ofthe clinical condition, the visual indication comprising a change to thecolor distribution of the cell, animate in real-time the dynamic imageon a map presented at the display device by presenting in sequence atleast two images of the plurality of images of the dynamic image, andpresent in real-time, on the map, the visual indication of the potentialfuture status of the clinical condition.
 14. The patient monitoringsystem of claim 13, wherein the clinical condition is sepsis.
 15. Thepatient monitoring system as in claim 13, wherein the instructions, whenexecuted, further cause the patient monitoring system to determine aprobability of the potential future status of the clinical condition andpresent the probability on the map with the visual indication of thepotential future status of the clinical condition.
 16. The patientmonitoring system of claim 13, wherein: each image of the plurality ofimages corresponds to a point-in-time of a plurality of points-in-time;the map comprises a two-dimensional map and a time axis at which one ofthe plurality of points-in-time is selectable; and the instructions,when executed, further cause the patient monitoring system to present,at the display device in response to receipt of user input selecting oneof the plurality of points-in-time, one of the plurality of images thatcorresponds to the selected point-in-time.
 17. The patient monitoringsystem of claim 15, wherein the clinical condition is sepsis.
 18. Thepatient monitoring system of claim 13, wherein: the instructions, whenexecuted, further cause the patient monitoring system to present, at thedisplay device on a two-dimensional map comprising a time axis, a seconddynamic image visually depicting the clinical condition during a timeperiod comprising one or more of the plurality of points-in-time, thesecond dynamic image comprising a second time series of a plurality ofsecond images, each second image of the plurality of second imagescorresponding to one of the plurality of points-in-time and presentedalong the time axis at a corresponding point-in-time.
 19. The patientmonitoring system of claim 13, wherein the visual indication of thefuture status of the clinical condition further comprises a change to asize or a shape of the cell.
 20. A real-time patient monitoring systemcomprising: a real-time patient monitor communicatively coupled to aplurality of measurement devices, the patient monitor having a displaydevice, a memory to store instructions, and one or more processorscommunicatively coupled to the memory and the display; and a storagedevice in communication with the patient monitor configured to storehistorical physiologic and laboratory data values about a plurality ofphysiological systems of a patient; wherein the instructions, whenexecuted by the one or more processors, cause the patient monitoringsystem to receive in real-time a plurality of time series, each timeseries being biologic particle density values of a biologic particletype associated with the patient; generate a plurality of perturbationsby identifying changes in the biological particle density values of theplurality of time series; determine, for each perturbation, a pluralityof properties of the perturbation, wherein the properties include atleast one of a slope, a magnitude, a percent change, a change duration,a minimum, a maximum, and a change relative to a normal range for thebiologic particle density of the biologic particle type; assign aseverity value to each determined property of each perturbation, whereinthe severity values correspond to the severity of the determinedproperty with respect to at least one physiological system; generate inreal-time a plurality of sequential severity profiles over time for eachphysiological system, each severity profile responsive to severityvalues of the properties of the perturbations associated with thephysiological system; display, on the display device, a two-dimensionalmap having a horizontal time axis and one or more columns extendingacross the horizontal time axis, wherein each column corresponds to agiven time period, the two-dimensional map further having a plurality ofrows, each row corresponding to one of the physiological systems;generate an image for each of the plurality of sequential severityprofiles, each image having one or more cells arranged perpendicular tothe horizontal time axis and having a width equal to the width of theone or more columns, wherein the number of the one or more cells and thecolor of each of the one or more cells are based on one or more of thedetermined perturbations, the determined properties of eachperturbation, the assigned severity values of each property, or thedetermined severity profile of each physiological system; and display inreal-time, across the one or more columns, a sequence of the generatedimages for the sequential severity profiles associated with thephysiological systems corresponding to the time period of each columnsuch that the sequence of generated images visually depict aseverity-centric progression of the physiological systems over time.